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)

Research at Dept. of Computational Sciences

Research Outcome

Total Numbers

Publications

157

Books

8

Book Chapters

18

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

100+

Cumulative Impact Factor

380+

Publications in other Journals

20

Patents applied/granted

9

Full papers in conference proceedings

30

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 Applications81(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 Applications81(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 Computing26(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 Informatics68, 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 Applications81(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 Applications34(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. SADHANA47(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 Applications198, 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 Fusion79, 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 Applications191, 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 Systems8(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
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  • Year 2017
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  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

  5. S. Kataria, Munish Kumar and N. K. Garg, “Writer identification System for Handwritten Gurmukhi Characters: Study of Different Feature-Classifier Combinations”, International Conference on Computational Intelligence & Data Engineering (ICCIDE-2017), pp. 125-131,2017 https://link.springer.com/chapter/10.1007/978-981-10-6319-0_11
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  • Year 2016

  1. Munish Kumar, R. K. Sharma and M. K. Jindal, “A Framework for Grading Writers using Offline Gurmukhi Characters”, Proceedings of the National Academy of Sciences- Physical Science- A, Vol. 86(3), pp. 405-415, 2016. (SCI Indexed https://link.springer.com/article/10.1007/s40010-016-0277-x

  • Year 2014
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  1. Munish Kumar, R. K. Sharma and M. K. Jindal, “Efficient Feature Extraction Techniques for Offline Handwritten Gurmukhi Character Recognition”, National Academy Science Letters, Vol. 37(4), pp. 381-391, 2014. (SCI Indexed https://link.springer.com/article/10.1007/s40009-014-0253-4

  2. Munish Kumar, R. K. Sharma and M. K. Jindal, “A Novel Hierarchical Technique for Offline Handwritten Gurmukhi Character Recognition”, National Academy Science Letters, Vol. 37(6), pp. 567-572, 2014. (SCI Indexed https://link.springer.com/article/10.1007/s40009-014-0280-1

  3. S. Bansal, M. Garg and Munish Kumar, “A Technique for Offline Handwritten Character Recognition”, International Journal of Computing and Technology, Vol. 1(2), pp. 210-215,2014 https://www.semanticscholar.org/paper/A-Technique-for-Offline-Handwritten-Character-Bansal-Garg/30e83335e6caa383b486fa174d0ffce95919f800

  • Year 2013

  1. Munish Kumar, R. K. Sharma and M. K. Jindal, “A Novel Feature Extraction Technique for Offline Handwritten Gurmukhi Character Recognition”, IETE Journal of Research, Vol. 59(6), pp. 687-692, 2013. (SCI Indexed https://www.tandfonline.com/doi/abs/10.4103/0377-2063.126961

  2. Munish Kumar, R. K. Sharma and M. K. Jindal, “Size of Training set vis-Övis Recognition Accuracy of Handwritten Character Recognition System”, Journal of Emerging Technologies in Web Intelligence, Vol. 5(4), pp. 380-384,2013 http://www.jetwi.us/index.php?m=content&c=index&a=show&catid=148&id=781
  3. Munish Kumar, M. K. Jindal and R. K. Sharma, “MDP Feature Extraction Technique for Offline Handwritten Gurmukhi Character Recognition”, Smart Computing Review, Vol. 3(6), pp. 397-404,2013.
  4. Munish Kumar, R. K. Sharma and M. K. Jindal, “Segmentation of Isolated and Touching Characters in Offline Handwritten Gurmukhi ScriptRecognition”, International Journal of Information Technology and Computer Science, Vol. 2, pp. 58-63, 2013.
  5. Munish Kumar, M. K. Jindal and R. K. Sharma, “PCA Based Offline Handwritten Gurmukhi Character Recognition System”, Smart Computing Review, Vol. 3(5), pp. 346- 357,2013 http://www.mecs-press.org/ijitcs/ijitcs-v6-n2/IJITCS-V6-N2-8.pdf 
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Year 2012

  1. Munish Kumar, M. K. Jindal and R. K. Sharma, “Weka based Offline Handwritten Gurmukhi Character Recognition”, Proceedings of International Conference on Soft Computing for Problem Solving, pp. 711-720,2012 https://link.springer.com/chapter/10.1007/978-81-322-1602-5_76
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  • Year 2011

  1. Munish Kumar, M. K. Jindal and R. K. Sharma, “k-Nearest Neighbour Based Offline Handwritten Gurmukhi Character Recognition”, Proceedings of International Conference on Image Information Processing, Jaypee University of Information Technology, Waknaghat (Shimla), pp. 1-4,2011 https://ieeexplore.ieee.org/document/6108863

  2. Munish Kumar, R. K. Sharma and M. K. Jindal, “Classification of Characters and Grading Writers in Offline Handwritten Gurmukhi Script”, Proceedings of International Conference on Image Information Processing, Jaypee University of Information Technology, Waknaghat (Shimla), pp. 1-4,2011 https://ieeexplore.ieee.org/document/6108859

  3. Munish Kumar, M. K. Jindal and R. K. Sharma, “Offline Handwritten Gurmukhi Character Recognition Using CurvatureFeature”, Proceedings of International Conference on Advances in Modeling, Optimization and Computing, IIT Roorkee, pp. 981- 989, 2011.

  4. Munish Kumar, M. K. Jindal and R. K. Sharma, “Review on OCR for Handwritten Indian Scripts Character Recognition”, Proceedings of the First International Conference on Digital Image Processing and Pattern Recognition, DPPR, Vol. 205, pp. 268-276,2011. https://link.springer.com/chapter/10.1007%2F978-3-642-24055-3_28
  5. Munish Kumar, R. K. Sharma and M. K. Jindal, “SVM based Offline Handwritten Gurmukhi Character Recognition”, Proceedings of International Workshop on Soft Computing Applications and Knowledge Discovery, National Research University Higher School of Economics, Moscow (Russia), pp. 51-62, 2011 https://www.semanticscholar.org/paper/SVM-Based-Offline-Handwritten-Gurmukhi-Character-Kumar-Jindal/9de4d1b45832c8f27730c0b6ae38d70f59c476a4
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Year 2010

  1. Munish Kumar, R. K. Sharma and M. K. Jindal, “Segmentation of Lines and Words in Handwritten Gurmukhi Script Documents”, Proceedings of the First International Conference on Intelligent Interactive Technologies and Multimedia, Allahabad, pp. 28-30, 2010 https://dl.acm.org/doi/abs/10.1145/1963564.1963568

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