Maharaja Ranjit Singh Punjab Technical University, BATHINDA

(A State University Established By Govt. of Punjab vide Punjab Act No. 5 of 2015 and Approved Under Section 2(f) & 12 (B) of UGC)

Admissions
Registration 2024-25 Admission
Pre Registration 2024-25 Online Courses

Research at Dept. of Computational Sciences

Research Outcome

Total Numbers

Publications

157

Books

7

Book Chapters

24

Publications with Impact Factors in Journals indexed in SCOPUS, SCI, SSCI and ESCI

100+

Cumulative Impact Factor

400+

Publications in other Journals

20

Patents applied/granted

05 + 01 Filed

Full papers in conference proceedings

60+

Year 2024

  1. Dargan, S., & Kumar, M. (2024). Gender Classification System Based on the Behavioral Biometric Modality: Application of Handwritten Text. ACM Transactions on Asian and Low-Resource Language Information Processing, 23(3), 1-21.

  2. Dargan, S., Kumar, M., Mittal, A., & Kumar, K. (2024). Handwriting-based gender classification using machine learning techniques. Multimedia Tools and Applications, 83(7), 19871-19895.

  3. Farooq, U., Khurana, S. S., Singh, P., & Kumar, M. (2024). An Empirical Study on Detection of Android Adware Using Machine Learning Techniques. Multimedia Tools and Applications, 83(13), 38753-38792.

  4. Farooq, U., Singh, P., Khurana, S. S., & Kumar, M. (2024). Detection of content-based cybercrime in Roman Kashmiri using ensemble learning. Multimedia Tools and Applications, 83(11), 33071-33105.

  5. Kaur, H., Rani, V., Kumar, M., Sachdeva, M., Mittal, A., & Kumar, K. (2024). Federated learning: a comprehensive review of recent advances and applications. Multimedia Tools and Applications, 83(18), 54165-54188.

  6. Kaur, M., & Kumar, M. (2024). Facial emotion recognition: A comprehensive review. Expert Systems, e13670.

  7. Liu, J., Xu, Z., Yang, Y., Zhou, K., & Kumar, M. (2024). Dynamic Prediction Model of Financial Asset Volatility Based on Bidirectional Recurrent Neural Networks. Journal of Organizational and End User Computing (JOEUC), 36(1), 1-23.

  8. Nabi, S. T., Kumar, M., & Singh, P. (2024). A convolution deep architecture for gender classification of urdu handwritten characters. Multimedia Tools and Applications, 1-16.

  9. Rani, V., Kumar, M., Gupta, A., Sachdeva, M., Mittal, A., & Kumar, K. (2024). Self-supervised learning for medical image analysis: a comprehensive review. Evolving Systems, 1-27.

  10. Shaheed, K., Abbas, Q., & Kumar, M. (2024). Automatic diagnosis of CoV-19 in CXR images using haar-like feature and XgBoost classifier. Multimedia Tools and Applications, 1-23.

  11. Shaheed, K., Szczuko, P., Kumar, M., Qureshi, I., Abbas, Q., & Ullah, I. (2024). Deep learning techniques for biometric security: A systematic review of presentation attack detection systems. Engineering Applications of Artificial Intelligence, 129, 107569.

  12. Sidhu, S., Khurana, S. S., Kumar, M., Singh, P., & Bamber, S. S. (2024). Sentiment analysis of Hindi language text: a critical review. Multimedia Tools and Applications, 83(17), 51367-51396.

  13. Singh, P., Singh, P., Farooq, U., Khurana, S. S., Verma, J. K., & Kumar, M. (2024). Retraction Note: CottonLeafNet: cotton plant leaf disease detection using deep neural networks.

  14. Singh, S., Garg, N. K., & Kumar, M. (2024). VGG16: Offline handwritten devanagari word recognition using transfer learning. Multimedia Tools and Applications, 1-34.

  15. Singla, C., Maini, R., & Kumar, M. (2024). Age, gender and handedness prediction using handwritten text: A comprehensive survey. Engineering Applications of Artificial Intelligence, 128, 107432.

Year 2023

  1. Kaur, H., Bansal, S., Kumar, M., Mittal, A., & Kumar, K. (2023). Worddeepnet: handwritten  gurumukhi word recognition using convolutional neural network. Multimedia Tools and  Applications, 82(30), 46763-46788.  

  2. Kaur, H., Rani, V., Kumar, M., Sachdeva, M., Mittal, A., & Kumar, K. (2023). Federated  learning: a comprehensive review of recent advances and applications. Multimedia Tools and  Applications, 1-24.  

  3. Sidhu, S., Khurana, S. S., Kumar, M., Singh, P., & Bamber, S. S. (2023). Sentiment analysis  of Hindi language text: a critical review. Multimedia Tools and Applications, 1-30.
  4.  Naman, S., Sharma, S., Kumar, M., Kumar, M., & Baldi, A. (2023). Developing a CNN-Based  Machine Learning Model for Cardamom Identification: A Transfer Learning Approach. Latin  American Journal of Pharmacy: A Life Science Journal, 42(6), 565-574.  
  5.  Farooq, U., Khurana, S. S., Singh, P., & Kumar, M. (2023). An Empirical Study on Detection of  Android Adware Using Machine Learning Techniques. Multimedia Tools and Applications, 1- 40.  
  6. Singh, P., Singh, P., Farooq, U., Khurana, S. S., Verma, J. K., & Kumar, M. (2023).  CottonLeafNet: cotton plant leaf disease detection using deep neural networks. Multimedia  Tools and Applications, 82(24), 37151-37176.
  7. Rani, V., & Kumar, M. (2023). Human gait recognition: A systematic review. Multimedia Tools  and Applications, 82(24), 37003-37037.
  8.  Mohiuddin, S., Malakar, S., Kumar, M., & Sarkar, R. (2023). A comprehensive survey on state of-the-art video forgery detection techniques. Multimedia Tools and Applications, 82(22), 33499-33539
  9. Kumar, M., Jindal, M. K., & Kumar, M. (2023). An efficient technique for breaking of coloured  Hindi CAPTCHA. Soft Computing, 27(16), 11661-11686.  
  10. Singh, N., Kumar, M., Singh, B., & Singh, J. (2023). DeepSpacy-NER: an efficient deep  learning model for named entity recognition for Punjabi language. Evolving Systems, 14(4),  673-683.  
  11. Kaur, R. P., Kumar, M., & Jindal, M. K. (2023). Performance evaluation of different features  and classifiers for Gurumukhi newspaper text recognition. Journal of Ambient Intelligence and  Humanized Computing, 14(8), 10245-10261. 
  12. Kaur, H., Kumar, M., Gupta, A., Sachdeva, M., Mittal, A., & Kumar, K. (2023). Bagging: An  Ensemble Approach for Recognition of Handwritten Place Names in Gurumukhi Script. ACM  Transactions on Asian and Low-Resource Language Information Processing, 22(7), 1-25.
  13. Nabi, S. T., Singh, P., & Kumar, M. (2023, July). Writer Identification from Offline Handwriting  Images in Urdu Script with Dense-Net: A Deep Learning Approach. In 2023 14th International  Conference on Computing Communication and Networking Technologies (ICCCNT) (pp. 1-6).  IEEE. 
  14. Kaur, A., Kumar, M., & Jindal, M. K. (2023). Cattle identification system: a comparative analysis  of SIFT, SURF and ORB feature descriptors. Multimedia Tools and Applications, 82(18),  27391-27413.  
  15. Maqbool, J., Mann, T. S., Kaur, N., Gupta, A., Mittal, A., Aggarwal, P., Kumar, M & Saini, S. S.  (2023). SegCon: A Novel Deep Neural Network for Seg mentation of Con junctiva Region.  In Advances in Data-driven Computing and Intelligent Systems: Selected Papers from ADCIS  2022, Volume 2 (pp. 719-730). Singapore: Springer Nature Singapore.  
  16. Nabi, S. T., Singh, P., & Kumar, M. (2023, May). Gender Classification from Offline Handwriting  Images in Urdu Script: LeNet-5 and Alex-Net. In 2023 3rd International Conference on Applied  Artificial Intelligence (ICAPAI) (pp. 1-6). IEEE. 
  17. Sethi, M., Kumar, M., & Jindal, M. K. (2023). Gender prediction system through behavioral  biometric handwriting: a comprehensive review. Soft Computing, 27(10), 6307-6327.  
  18. Nabi, S. T., Kumar, M., & Singh, P. (2023). DeepNet-WI: A deep-net model for offline Urdu  writer identification. Evolving Systems, 1-11. 
  19.  Singh, S., Garg, N. K., & Kumar, M. (2023). On the performance analysis of various features  and classifiers for handwritten Devanagari word recognition. Neural Computing and  Applications, 35(10), 7509-7527.  
  20.  Bansal, M., Kumar, M., Sachdeva, M., & Mittal, A. (2023). Transfer learning for image  classification using VGG19: Caltech-101 image data set. Journal of ambient intelligence and  humanized computing, 1-12. 

  21. Sitender, Bawa, S., Kumar, M., & Sangeeta. (2023). A comprehensive survey on machine  translation for English, Hindi and Sanskrit languages. Journal of Ambient Intelligence and  Humanized Computing, 14(4), 3441-3474.  

  22. Rani, V., & Kumar, M. (2023, March). DeepNet-Gait: Human Identification by Gait Using  Convolutional Neural Network Model. In 2023 10th International Conference on Signal  Processing and Integrated Networks (SPIN) (pp. 115-120). IEEE.  

  23. Kaur, A., Kumar, M., & Jindal, M. K. (2023, March). Analytical Study of Hybrid Features and  Classifiers for Cattle Identification. In International Conference on Communications and Cyber  Physical Engineering 2018 (pp. 623-631). Singapore: Springer Nature Singapore.  
  24. Singh, A., Kukreja, V., & Kumar, M. (2023). An empirical study to design an effective agile  knowledge management framework. Multimedia tools and applications, 82(8), 12191-12209.
  25.  Kaur, G., Singh, N., & Kumar, M. (2023). Image forgery techniques: a review. Artificial  Intelligence Review, 56(2), 1577-1625. 
  26. Kaur, H., & Kumar, M. (2023). Signature identification and verification techniques: state-of-the art work. Journal of Ambient Intelligence and Humanized Computing, 14(2), 1027-1045.  
  27. Sandhu, J. K., Singh, A., & Kumar, M. (2023). An Efficient Speech Enhancement Approach for  Punjabi Language Using Acoustic and Tonal Features. NeuroQuantology, 21(6), 1527.  
  28. Dhalla, S., Maqbool, J., Mann, T. S., Gupta, A., Mittal, A., Aggarwal, P., Kumar, M & Saini, S.  S. (2023). Semantic segmentation of palpebral conjunctiva using predefined deep neural  architectures for anemia detection. Procedia Computer Science, 218, 328-337.  
  29. Rani, V., Nabi, S. T., Kumar, M., Mittal, A., & Kumar, K. (2023). Self-supervised learning: A  succinct review. Archives of Computational Methods in Engineering, 30(4), 2761-2775.
  30. Dargan, S., Bansal, S., Kumar, M., Mittal, A., & Kumar, K. (2023). Augmented reality: A  comprehensive review. Archives of Computational Methods in Engineering, 30(2), 1057-1080. 
  31. Walia, S., Kumar, K., & Kumar, M. (2023). Unveiling digital image forgeries using Markov based  quaternions in frequency domain and fusion of machine learning algorithms. Multimedia Tools  and Applications, 82(3), 4517-4532

  32.  Misgar, M. M., Mushtaq, F., Khurana, S. S., & Kumar, M. (2023). Recognition of offline  handwritten Urdu characters using RNN and LSTM models. Multimedia Tools and  Applications, 82(2), 2053-2076.  

  33.  Sethi, M., Jindal, M. K., & Kumar, M. (2022, June). Feature extraction techniques for gender  classification based on handwritten text: a critical review. In Proceedings of International  Conference on Frontiers in Computing and Systems: COMSYS 2021 (pp. 191-201). Singapore:  Springer Nature Singapore.  

  34. Singh, S., Garg, N. K., & Kumar, M. (2023). Feature extraction and classification techniques  for handwritten Devanagari text recognition: a survey. Multimedia Tools and  Applications, 82(1), 747-775.

  35. Rani, S., Kaur, M., Kumar, M., Ravi, V., Ghosh, U., & Mohanty, J. R. (2023). Detection of  shilling attack in recommender system for YouTube video statistics using machine learning techniques. Soft Computing, 27(1), 377-389.                 

Year 2022

1. Dhiman, B., Kumar, Y., & Kumar, M.. (2022). Fruit Quality  Evaluation Using Machine Learning Techniques: Review, Motivation and future perspectives. Multimedia Tools and Applications, 81(12), 16255–16277. (SCI Indexed) https://doi.org/10.1007/s11042-022-12652-2

2. Jan, T. G., Khurana, S. S., & Kumar, M. (2022). Semi-supervised labeling: A proposed methodology for labeling the Twitter datasets. Multimedia Tools and Applications, 81(6), 7669–7683. (SCI Indexed) https://doi.org/10.1007/s11042-022-12221-7

3. Kaur, A., Kumar, M., & Jindal, M. K. (2022). Cattle identification muzzle pattern using Computer Vision Technology: A critical review and prospective. Soft Computing, 26(10), 4771–4795. (SCI Indexed)  https://doi.org/10.1007/s00500-022-06935-x

4. Kaur, A., Kumar, M., & Jindal, M. K. (2022). Shi-Tomasi Corner detector for cattle identification from muzzle print image pattern. Ecological Informatics, 68, 101549. (SCI Indexed)  https://doi.org/10.1016/j.ecoinf.2021.101549

5. Kaur, G., Singh, N., & Kumar, M. (2022). Image forgery techniques: A Review. Artificial Intelligence Review. (SCI Indexed) https://doi.org/10.1007/s10462-022-10211-7

6. Kaur, R. P., Kumar, M., & Jindal, M. K. (2022). Performance evaluation of different features and classifiers for Gurumukhi Newspaper Text Recognition. Journal of Ambient Intelligence and Humanized Computing.  (SCI Indexed)  https://doi.org/10.1007/s12652-021-03687-8

7. Koul, S., Kumar, M., Khurana, S. S., Mushtaq, F., & Kumar, K. (2022). An efficient approach for copy-move image forgery detection using Convolution Neural Network. Multimedia Tools and Applications, 81(8), 11259–11277. (SCI Indexed) https://doi.org/10.1007/s11042-022-11974-5

8. Kumar, M., Jindal, M. K., & Kumar, M. (2022). Design of innovative CAPTCHA for Hindi language. Neural Computing and Applications, 34(6), 4957–4992. (SCI Indexed) https://doi.org/10.1007/s00521-021-06686-0

9. Kumar, M., Jindal, M. K., & Kumar, M. (2022). Distortion, rotation and scale-invariant recognition of hollow Hindi characters. SADHANA, 47(2). (SCI Indexed) https://doi.org/10.1007/s12046-022-01847-w

10. Misgar, M. M., Mushtaq, F., Khurana, S. S., & Kumar, M. (2022). Recognition of offline handwritten Urdu characters using RNN and LSTM models. Multimedia Tools and Applications.  (SCI Indexed) https://doi.org/10.1007/s11042-022-13320-1

11. Rani, V., Kumar, M., Mittal, A., & Kumar, K. (2022). Artificial Intelligence for cybersecurity: Recent advancements, challenges and opportunities. Robotics and AI for Cybersecurity and Critical Infrastructure in Smart Cities, 73–88. (SCI Indexed) https://doi.org/10.1007/978-3-030-96737-6_4

12. Shaheed, K., Mao, A., Qureshi, I., Abbas, Q., Kumar, M., & Zhang, X. (2022). Finger-vein presentation attack detection using depthwise separable convolution neural network. Expert Systems with Applications, 198, 116786. (SCI Indexed) https://doi.org/10.1016/j.eswa.2022.116786

13. Shaheed, K., Mao, A., Qureshi, I., Kumar, M., Hussain, S., & Zhang, X. (2022). Recent advancements in finger vein recognition technology Methodology, challenges and opportunities. Information Fusion, 79, 84–109. (SCI Indexed) https://doi.org/10.1016/j.inffus.2021.10.004

14. Shaheed, K., Mao, A., Qureshi, I., Kumar, M., Hussain, S., Ullah, I., & Zhang, X. (2022). DS-CNN: A pre-trained XCEPTION model based on depth-wise separable convolutional neural network for finger vein recognition. Expert Systems with Applications, 191, 116288. (SCI Indexed)  https://doi.org/10.1016/j.eswa.2021.116288

15. Singh, A., Kaur, N., Kukreja, V., Kadyan, V., & Kumar, M. (2022). Computational intelligence in processing of Speech Acoustics: A survey. Complex & Intelligent Systems, 8(3), 2623–2661. (SCI Indexed)  https://doi.org/10.1007/s40747-022-00665-1 

16. Singh, S., Garg, N. K., & Kumar, M. (2022). Feature extraction and classification techniques for handwritten Devanagari text recognition: A survey. Multimedia Tools and Applications. (SCI Indexed)  https://doi.org/10.1007/s11042-022-13318-9

Year 2021

  1. Chaturvedi, V., Kaur, A. B., Varshney, V., Garg, A., Chhabra, G. S., & Kumar, M. (2021). Music mood and human emotion recognition based on physiological signals: A systematic review. Multimedia Systems, 28(1), 21–44. (SCI Indexed)  https://doi.org/10.1007/s00530-021-00786-6

  2. Kumar, M., Jindal, M. K., & Kumar, M. (2021). A systematic survey on CAPTCHA RECOGNITION: Types, creation and breaking techniques. Archives of Computational Methods in Engineering, 29(2), 1107–1136. (SCI Indexed)https://doi.org/10.1007/s11831-021-09608-4

  3. M. Bansal, Munish Kumar, and M. Kumar, "2D object recognition: a comparative analysis of SIFT, SURF and ORB feature descriptors", Multimedia Tools and Applications, 2021 (SCI Indexed) https://link.springer.com/article/10.1007%2Fs11042-021-10646-0

  4. Y. Kumar, N. Singh, Munish Kumar, and A. Singh, “AutoSSR: an efficient approach for automatic spontaneous speech recognition model for the Punjabi Language”, Soft Computing, Vol. 25, pp. 1617–1630, 2021 (SCI Indexed) https://link.springer.com/article/10.1007/s00500-020-05248-1

  5. M. Mittal, Munish Kumar, A. Verma, I. Kaur, B. Kaur, M. Sharma and L. M. Goyal, “FEMT: a computational approach for fog elimination using multiple thresholds”, Multimedia Tools and Applications, Vol. 80, pp. 227–241, 2021 (SCI Indexed) https://link.springer.com/article/10.1007/s11042-020-09657-0

  6. M. Arora and Munish Kumar, “AutoFER: PCA and PSO Based Automatic Facial Emotion Recognition”, Multimedia Tools and Applications, Vol. 80, pp. 3039–3049, 2021.(SCI Indexed) https://link.springer.com/article/10.1007/s11042-020-09726-4

  7. H. Kaur and Munish Kumar “On the Recognition of Offline Handwritten Word Using Holistic Approach and AdaBoost Methodology”, Multimedia Tools and Applications, 2021 (In Press), (SCI Indexed) https://link.springer.com/article/10.1007/s11042-020-10297-7

  8. A. Kumar, Munish Kumar, A. Kaur “Face Detection in Still Images under Occlusion and non-uniform illumination” Multimedia Tools and Applications, 2021(In Press), (SCI Indexed) https://link.springer.com/article/10.1007/s11042-020-10457-9

  9. S. Rani, M. Kaur and Munish Kumar “Detection of Shilling Attack in Recommender System for YouTube Video Statistics using Machine Learning Techniques”, Soft Computing, 2021 (In Press), (SCI Indexed) https://link.springer.com/article/10.1007/s00500-021-05586-8

  10. K. Kapoor, S. Rani, Munish Kumar, V. Chopra and G. S. Brar “Hybrid Local Phase Quantization and Grey Wolf Optimization Based SVM for Finger Vein Recognition”, Multimedia Tools and Applications, 2021 (In Press), (SCI Indexed) https://link.springer.com/article/10.1007/s11042-021-10548-1

  11. H. Singh, R. K. Sharma, V. P. Singh and Munish Kumar “Recognition of Online Handwritten Gurmukhi Characters Using Recurrent Neural Network”, Soft Computing, 2021 (In Press), (SCI Indexed) https://link.springer.com/article/10.1007/s00500-021-05620-9

  12. Munish Kumar, N. Singh, R. Kumar, S. Goel and K. Kumar “Gait Recognition Based on Vision Systems: A Systematic Survey”, Journal of Visual Communication and Image Representation, Vol. 75, pp. 103052, 2021, (SCI Indexed).https://www.sciencedirect.com/science/article/abs/pii/S1047320321000249

  13. M. Bansal, Munish Kumar and M. Kumar “2D Object Recognition: A Comparative Analysis of SIFT, SURF, and ORB Feature Descriptors”, Multimedia Tools and Applications, 2021(In Press), (SCI Indexed) https://link.springer.com/article/10.1007/s11042-021-10646-0

  14. L. M. Goyal, M. Mittal, Munish Kumar, B. Kaur, M. Sharma and A. Verma, "An Efficient Method of Multicolor Detection Using Global Optimum Thresholding For Image Analysis”, Multimedia Tools and Applications, 2021(In Press), (SCI Indexed) https://link.springer.com/article/10.1007/s11042-020-10365-y

  15. K. Shaheed, A. Mao, I. Qureshi, Munish Kumar, Q. Abbas, I. Ullah and X. Zhang, "A Systematic Review on Physiological-Based Biometric Recognition Systems: Current and Future Trends", Archives of Computational Methods in Engineering, 2021(In Press), (SCI Indexed) https://link.springer.com/article/10.1007/s11831-021-09560-3

  16. S. Singh, U. Ahuja, Munish Kumar, K. Kumar and M. Sachdeva, "Face mask detection using YOLOv3 and faster R-CNN models: COVID-19 environment", Multimedia Tools and Applications, 2021(In Press), (SCI Indexed). https://link.springer.com/article/10.1007/s11042-021-10711-8

  17. S. R. Narang, Munish Kumar, M. K. Jindal, "DeepNetDevanagari: a deep learning model for Devanagari ancient character recognition", Multimedia Tools and Applications, 2021(In Press), (SCI Indexed) https://link.springer.com/article/10.1007/s11042-021-10775-6.

Year 2020

  1. P. Chhabra, N. K. Garg and Munish Kumar, “Content-Based Image Retrieval System using ORB and SIFT Features”, Neural Computing and Applications, Vol. 32, pp. 2725–2733, 2020. (SCI Indexed) https://link.springer.com/article/10.1007/s00521-018-3677-9

  2. Munish Kumar and S. R. Jindal, “A Study of Recognition of Pre-Segmented Handwritten Multi-lingual Characters”, Archives of Computational Methods in Engineering, Vol. 27, pp. 577–589, 2020. (SCI Indexed) https://link.springer.com/article/10.1007/s11831-019-09332-0

  3. Munish Kumar, M. K. Jindal, R. K. Sharma, and S. R. Jindal, “Performance Evaluation of Classifiers for the Recognition of Offline Handwritten Gurumukhi Characters and Numerals: A Study”, Artificial Intelligence Review, Vol. 53, pp. 2075–2097, 2020. (SCI Indexed) https://link.springer.com/article/10.1007/s10462-019-09727-2

  4. A. Singh, V. Kadyan, Munish Kumar, and N. Baggan “ASRoIL: a comprehensive survey for automatic speech recognition of Indian languages”, Artificial Intelligence Review, Vol. 53, pp. 3673–3704, 2020. (SCI Indexed) https://link.springer.com/article/10.1007/s10462-019-09775-8

  5. S. Gupta and Munish Kumar, “Forensic document examination system using boosting and bagging methodologies”, Soft Computing, Vol. 24, pp. 5409–5426, 2020. (SCI Indexed) https://link.springer.com/article/10.1007/s00500-019-04297-5

  6. R. P. Kaur, Munish Kumar and M. K. Jindal, “Newspaper Text Recognition of Gurumukhi Script Using Random Forest Classifier”, Multimedia Tools and Applications, Vol. 79, pp. 7435–7448, 2020.(SCI Indexed) https://link.springer.com/article/10.1007/s11042-019-08365-8

  7. S. Dargan and Munish Kumar, “A comprehensive survey on the biometric recognition systems based on physiological and behavioral modalities”, Expert Systems with Applications, Vol. 143, 1131142020, 2020. (SCI Indexed) https://www.sciencedirect.com/science/article/abs/pii/S0957417419308310

  8. Munish Kumar, S. Gupta and N. Mohan, “A Computational Approach for Printed Document Forensics using SURF and ORB Features” Soft Computing, Vol. 24, pp. 13197-13208, 2020 (SCI Indexed) https://link.springer.com/article/10.1007/s00500-020-04733-x

  9. S. Gupta, K. Thakur and Munish Kumar, “2D-Human Face Recognition Using SIFT and SURF descriptors of Face’s Feature Regions” The Visual Computer, pp. 1-10, 2020 (In Press), (SCI Indexed) https://link.springer.com/article/10.1007/s00371-020-01814-8

  10. M. Bansal, Munish Kumar, and M. Kumar, “2D Object Recognition Techniques: State- of-the-Art Work”, Archives of Computational Methods in Engineering, pp. 1-15, 2020 (In Press), (SCI Indexed) https://link.springer.com/article/10.1007/s11831-020-09409-1

  11. S. R. Narang, M. K. Jindal and Munish Kumar, “Ancient Text Recognition: A Review” Artificial Intelligence Review, Vol. 53, pp. 5517–5558,2020. DOI: 10.1007/s10462020-09827-4 (SCI Indexed) https://link.springer.com/article/10.1007/s10462-020-09827-4

  12. I. R. Parray, S. Singh and Munish Kumar, “Time Series Data Analysis of Stock Price Movement Using Machine Learning Techniques”, Soft Computing, Vol. 24, pp. 16509- 16517, 2020. (SCI Indexed) https://link.springer.com/article/10.1007/s00500-020-04957-x

  13. S. R. Narang, M. K. Jindal, S. Ahuja, and Munish Kumar, “On the Recognition of Devanagari Ancient Handwritten Characters using SIFT and Gabor Features”, Soft Computing, Vol. 24, pp. 17279-17289, 2020 (SCI Indexed https://link.springer.com/article/10.1007/s00500-020-05018-z

  14. S. Gupta, N. Mohan and Munish Kumar, “A Study on Source Device Attribution using Still Images”, Archives of Computational Methods in Engineering, 2020. (SCI Indexed https://link.springer.com/article/10.1007/s11831-020-09452-y

  15. R. P. Kaur, M. K. Jindal, and Munish Kumar, “Text and Graphics Segmentation of Newspaper Printed in Gurmukhi Script: A Hybrid Approach”, The Visual Computer, 2020 (In Press), (SCI Indexed https://link.springer.com/article/10.1007/s00371-020-01927-0

  16. H. Kaur and Munish Kumar, “Offline Handwritten Gurumukhi Word Recognition Using eXtreme Gradient Boosting Methodology”, Soft Computing, 2020 (In Press), (SCI Indexed) https://link.springer.com/article/10.1007/s00500-020-05455-w

  17. M. Bansal, Munish Kumar, M. Kumar, K. Kumar “An Efficient Technique for Object Recognition Using Shi-Tomasi Corner Detection Algorithm”, Soft Computing, 2020 (In Press), (SCI Indexed) https://link.springer.com/article/10.1007/s00500-020-05453-y

  18. Munish Kumar, S. Gupta, K. Kumar and M. Sachdeva, “Spreading of Covid-19 in India, Italy, Japan, Spain, UK, US: A Prediction Using ARIMA and LSTM Model”, Digital Government: Research and Practice, Article No. 24,2020 https://dl.acm.org/doi/10.1145/3411760

  19. R. P. Kaur, M. K. Jindal and Munish Kumar, “Newspaper Text Recognition of Gurumukhi Script using Random Forest Classifier”, Proceedings of International Conference on Machine Intelligence and Data Science Applications (MIDAS-2020),2020.
  20. R. P. Kaur, M. K. Jindal and Munish Kumar, “TxtLineSeg: Text Line Segmentation of Unconstrained Printed Text in Devanagari Script”, Proceedings of International Conference on Computational Methods and Data Engineering, pp. 85-100,2020.
  21. H. Kaur and Munish Kumar, “Offline Handwritten Gurumukhi Place Names Recognition using Curve Fitting Based Features”, Proceedings of International Conference on Robotics, Machine Learning and Artificial Intelligence,2020 https://link.springer.com/chapter/10.1007%2F978-981-15-7907-3_7
  22. M. Bansal, Munish Kumar, and M. Kumar “XGBoost: 2D-Object Recognition using Shape Descriptors and Extreme Gradient Boosting Classifier”, Proceedings of International Conference on Computational Methods and Data Engineering, pp. 207-222, 2020.
  23. H. Kaur and Munish Kumar, “Feature Selection Techniques for Offline Handwritten Gurumukhi Place Name Recognition”, Proceedings of International Conference on Machine Intelligence and Data Science Applications (MIDAS-2020),2020.
  24. S. Dargan and Munish Kumar, “Writer Identification System Based on Offline handwritten Text in Gurumukhi Script”, Proceedings of International Conference on Parallel, Distributed and Grid Computing (PDGC-2020),2020.
  25. M. Bansal, Munish Kumar, and M. Kumar “2D-Object Recognition: Performance Comparison of Various Feature Extraction Techniques for Caltech-101 Image Dataset”, Proceedings of International Conference on Advances and Applications of Artificial Intelligence & Machine Learning, pp. 207-222,2020 https://link.springer.com/chapter/10.1007/978-981-15-6876-3_16 

  26. S. Dargan and Munish Kumar, “Writer Identification System Based on Offline handwritten Text in Gurumukhi Script”, Proceedings of International Conference on Parallel, Distributed and Grid Computing (PDGC-2020),2020.

  27. H. Singh, R. K. Sharma, R. Kumar, K. Verma, R. Kumar and Munish Kumar, “A Benchmark Dataset of Online Handwritten Gurmukhi Script Words and Numerals”, Proceedings of the International Conference on Computer Vision and Image Processing, 457- 466,2020. https://link.springer.com/chapter/10.1007/978-981-15-4018-9_41

Year 2019

  1. Munish Kumar, M. K. Jindal, R. K. Sharma and S. R. Jindal, “Character and Numeral Recognition for Non-Indic and Indic Scripts: A Survey”, Artificial Intelligence Review, Vol. 52(4), pp. 2235-2261, 2019. DOI: 10.1007/s10462-017-9607-x (SCI Indexed) https://link.springer.com/article/10.1007/s10462-017-9607-x
  2.  A. Kumar, A. Kaur and Munish Kumar, “Face Detection Techniques: A Review”, Artificial Intelligence Review, Vol. 52(2), pp. 927-948, 2019. (SCI Indexed https://link.springer.com/article/10.1007/s10462-018-9650-2
  3. Munish Kumar and S. R. Jindal, “Fusion of RGB and HSV Colour Space for Foggy Image Quality Enhancement”, Multimedia Tools and Applications, Vol. 78(8), pp. 9791- 9799, 2019. (SCI Indexed https://link.springer.com/article/10.1007/s11042-018-6599-8
  4. Munish Kumar, S. R. Jindal, M. K. Jindal and G. S. Lehal, “Improved Recognition Results of Medieval Handwritten Gurmukhi Manuscripts using Boosting and Bagging Methodologies”, Neural Processing Letters, Vol. 50(1), pp. 43-56, 2019. (SCI Indexed https://link.springer.com/article/10.1007/s11063-018-9913-6
  5. S. Dargon and Munish Kumar, “Writer Identification System for Indic and Non-Indic Scripts: State-of-the-art Survey”, Archives of Computational Methods in Engineering, Vol. 26(4), pp. 1283-1311, 2019. (SCI Indexed https://link.springer.com/article/10.1007/s11831-018-9278-z
  6. P. Kaur, R. Kumar and Munish Kumar, “A Healthcare Monitoring System using Random Forest and Internet of Things (IoT)”, Multimedia Tools and Applications, Vol. 78(14), pp. 19905-19916, 2019. (SCI Indexed https://link.springer.com/article/10.1007/s11042-019-7327-8
  7. S. Goel, R. Kumar, Munish Kumar and V. Chopra, “An Efficient Page Ranking Approach Based on Vector Norms using sNorm (p) Algorithm”, Information Processing and Management, Vol. 56(3), pp. 1053-1066, 2019. (SCI Indexed)https://www.sciencedirect.com/science/article/abs/pii/S0306457318305454
  8. S. R. Narang, M. K. Jindal and Munish Kumar, “Devanagari Ancient Character Recognition using DCT Features with Adaptive Boosting and Bootstrap Aggregating”, Soft Computing, Vol. 23, pp. 13603–13614, 2019. (SCI Indexed https://link.springer.com/article/10.1007/s00500-019-03897-5
  9. S. R. Narang, M. K. Jindal and Munish Kumar, “Devanagari Ancient Character Recognition using Statistical Feature Extraction Techniques”, SADHANA, Vol. 44: 141, 2019. (SCI Indexed https://www.ias.ac.in/describe/article/sadh/044/06/0141
  10. S. R. Narang, M. K. Jindal and Munish Kumar, “Drop Flow Method: An Iterative Algorithm for Complete Segmentation of Devanagari Ancient Manuscripts”, Multimedia Tools and Applications, Vol. 78(16), pp. 23255-23280, 2019. (SCI Indexed) https://link.springer.com/article/10.1007/s11042-019-7620-6
  11. S. Dargan, Munish Kumar, M. R. Ayyagari, and G. Kumar, “A Survey of Deep Learning and Its Applications: A New Paradigm to Machine Learning”, Archives of Computational Methods in Engineering, Vol. 27, pages1071–1092, 2019. (SCI Indexed https://link.springer.com/article/10.1007/s11831-019-09344-w
  12. R. P. Kaur, M. K. Jindal and Munish Kumar, “Recognition of Newspaper Printed in Gurmukhi Script”, Journal of Central South University, Vol. 26(9), pp. 2495-2503, 2019 (SCI Indexed) https://link.springer.com/article/10.1007/s11771-019-4189-1
  13. S. R. Narang, M. K. Jindal and Munish Kumar, “Line Segmentation of Devanagari Ancient Manuscript”, Proceedings of the National Academy of Sciences- Physical Science- A, Vol. 90, pp. 717–724, 2019. (SCI Indexed https://link.springer.com/article/10.1007/s40010-019-00627-2
  14. S. Gupta, Munish Kumar and A. Garg, “Improved Object Recognition Results using SIFT and ORB Feature Detector”, Multimedia Tools and Applications, Vol. 78, pp. 34157–34171, 2019. (SCI Indexed https://link.springer.com/article/10.1007/s11042-019-08232-6
  15. Munish Kumar, Surbhi Gupta, Xiao-Zhi Gao, Amitoj Singh, “Plant Species Recognition Using Morphological Features and Adaptive Boosting Methodology”, IEEE Access, Vol. 7, pp. 163912-163918, 2019. (SCI Indexed https://ieeexplore.ieee.org/document/8894140
  16. S. Dargan and Munish Kumar, A. Garg and K. Thakur, “Writer Identification System for Pre-Segmented Offline Handwritten Devanagari Characters using k-NN and SVM”, Soft Computing, Vol. 24, pp. 10111–10122, 2019.(SCI Indexed) https://link.springer.com/article/10.1007/s00500-019-04525-y

  17. H. Singh, R. K. Sharma and Munish Kumar, “A Benchmark Dataset of Online Handwritten Gurmukhi Script Words and Numerals”, Proceedings of the International Conference on Computer Vision and Image Processing, Jaipur, India,2019 https://link.springer.com/chapter/10.1007/978-981-15-4018-9_41

 

Year 2018

  1. Munish Kumar, M. K. Jindal and R. K. Sharma, “A Novel Handwriting Grading System Using Gurmukhi Characters”, International Arab Journal of Information Technology, Vol. 15 (6), pp. 945-950, 2018. (SCI Indexed http://iajit.org/index.phpoption=com_content&task=view&id=1635&Itemid=25
  2. Munish Kumar, M. K. Jindal, R. K. Sharma and S. R. Jindal, “Offline Handwritten Numeral Recognition using Combination of Different Feature Extraction Techniques”, National Academy Science Letters, Vol. 41(1), pp. 29-33, 2018. (SCI Indexed) https://link.springer.com/article/10.1007/s40009-017-0606-x
  3. Malika Arora, Munish Kumar and N. K. Garg, “Facial Emotion Recognition Based on PCA and Gradient Features”, National Academy Science Letters, Vol. 41 (6), pp. 365-368, 2018. (SCI Indexed https://link.springer.com/article/10.1007/s40009-018-0694-2
  4. Munish Kumar, P. Chhabra and N. K. Garg, “An Efficient Content Based Image Retrieval System Using BayesNet and K-NN”, Multimedia Tools and Applications, Vol. 77 (16), pp. 21557-21570, 2018. (SCI Indexed https://link.springer.com/article/10.1007/s11042-017-5587-8
  5. Diksha Garg, N. K. Garg and Munish Kumar, “Underwater Image Enhancement using Blending of CLAHE and Percentile Methodologies”, Multimedia Tools and Applications, Vol. 77 (20), pp. 26545-26561, 2018. (SCI Indexed https://link.springer.com/article/10.1007/s11042-018-5878-8
  6. H. Kaur and Munish Kumar, “A Comprehensive Survey on Word Recognition for non-Indic and Indic Scripts”, Pattern Analysis and Applications, Vol. 21(4), pp. 897-929, 2018. (SCI Indexed https://link.springer.com/article/10.1007/s10044-018-0731-2
  7. Munish Kumar, M. K. Jindal, R. K. Sharma and S. R. Jindal, “A Novel Framework for Writer Identification Based on Pre-Segmented Gurmukhi Characters”, SADHANA, Vol. 43(12), pp. 197, 2018. (SCI Indexed https://link.springer.com/article/10.1007/s12046-018-0966-z
  8. M. Khatri, Munish Kumar and A. Jain, “Pulmonary Lesion Detection and Staging from CT Images Using Watershed Algorithm”, Proceedings of the 8thInternational Conference on Advance Computing Conference (IACC), Benett University, Noida, pp. 108- 112,2018 https://ieeexplore.ieee.org/document/8692125
  9. Munish Kumar, M. K. Jindal, R. K. Sharma and S. R. Jindal, “Performance Comparison of Several Feature Selection Techniques for Offline Handwritten Character Recognition”, Proceedings of International Conference on Research in Intelligent and Computing in Engineering, pp. 1-6,2018. https://ieeexplore.ieee.org/document/8509076
  10. R. P. Kaur, M. K. Jindal and Munish Kumar, “Zone Segmentation of a Text line Printed in Gurmukhi Script Newspaper”, Proceedings of 5thInternational Conference on Parallel, Distributed and Grid Computing (PDGC-2018), Jaypee University of Information Technology, Waknaghat (Shimla), pp. 330-334,2018 https://ieeexplore.ieee.org/document/8745796
  11. Munish Kumar, R. K. Sharma, M. K. Jindal, S. R. Jindal and H. Singh, “Benchmark Datasets for Offline Handwritten Gurmukhi Script Recognition”, Proceedings of the Workshop on Document Analysis and Recognition, pp. 143-151,2018 https://link.springer.com/chapter/10.1007/978-981-13-9361-7_13
  12. H. Kaur and Munish Kumar, “Benchmark Dataset: Offline Handwritten Gurmukhi City Names for Postal Automation”, Proceedings of the Workshop on Document Analysis and Recognition, pp. 152-159,2018 https://link.springer.com/chapter/10.1007/978-981-13-9361-7_14

Year 2017

  1. Munish Kumar, R. K. Sharma and M. K. Jindal, “Offline Handwritten Gurmukhi Character Recognition: Analytical Study of different Transformations”, Proceedings of the National Academy of Sciences- Physical Science- A, Vol. 87(1), pp. 137-143, 2017. (SCI Indexed)https://link.springer.com/article/10.1007/s40010-016-0284-y
  2. Munish Kumar, M. K. Jindal and R. K. Sharma, “A Novel Technique for Line Segmentation in Offline Handwritten Gurmukhi Script Documents”, National Academy Science Letters, Vol. 40(4), pp. 273-277, 2017. (SCI Indexed https://link.springer.com/article/10.1007/s40009-017-0558-1
  3. Munish Kumar, and S. R. Jindal, “Devanagari Handwritten Grading System Based on Curvature Features”, Computer Modeling in Engineering & Sciences, Vol. 113 (2), pp. 201- 209, 2017. (SCI Indexed https://www.techscience.com/CMES/v113n2/27349

  4. S. Gupta, Y. J. Singh and Munish Kumar, “Object Detection Using Multiple Shape- Based Features”, Proceedings of International Conference on Parallel, Distributed and Grid Computing (PDGC-2018), Jaypee University of Information Technology, Waknaghat (Shimla), pp. 433-437,2017 https://ieeexplore.ieee.org/document/7913234

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