Segmentation and classification of medical images using texture-primitive features: Application of BAM-type artificial neural network N Sharma, AK Ray, S Sharma, KK Shukla, S Pradhan, LM Aggarwal Journal of medical physics 33 (3), 119-126, 2008 | 206 | 2008 |
Coverage and connectivity in WSNs: A survey, research issues and challenges A Tripathi, HP Gupta, T Dutta, R Mishra, KK Shukla, S Jit IEEE Access 6, 26971-26992, 2018 | 204 | 2018 |
Neuro-genetic prediction of software development effort KK Shukla Information and Software Technology 42 (10), 701-713, 2000 | 128 | 2000 |
Efficient algorithms for discrete wavelet transform: with applications to denoising and fuzzy inference systems KK Shukla, AK Tiwari Springer Science & Business Media, 2013 | 101 | 2013 |
Tolerance-based intuitionistic fuzzy-rough set approach for attribute reduction AK Tiwari, S Shreevastava, T Som, KK Shukla Expert Systems with Applications 101, 205-212, 2018 | 82 | 2018 |
Convergence rate analysis of proximal gradient methods with applications to composite minimization problems DR Sahu, JC Yao, M Verma, KK Shukla Optimization 70 (1), 75-100, 2021 | 78 | 2021 |
Prayas at emoint 2017: An ensemble of deep neural architectures for emotion intensity prediction in tweets P Goel, D Kulshreshtha, P Jain, KK Shukla Proceedings of the 8th workshop on computational approaches to subjectivity …, 2017 | 76 | 2017 |
Extended Karush-Kuhn-Tucker condition for constrained interval optimization problems and its application in support vector machines D Ghosh, A Singh, KK Shukla, K Manchanda Information Sciences 504, 276-292, 2019 | 71 | 2019 |
Passive copy-move forgery detection in videos RC Pandey, SK Singh, KK Shukla 2014 International conference on computer and communication technology …, 2014 | 68 | 2014 |
Classification of histopathological images of breast cancerous and non cancerous cells based on morphological features KK Shukla, A Tiwari, S Sharma Biomedical and Pharmacology Journal 10 (1), 353-366, 2017 | 61 | 2017 |
Fast and robust passive copy-move forgery detection using SURF and SIFT image features RC Pandey, SK Singh, KK Shukla, R Agrawal 2014 9th International conference on industrial and information systems …, 2014 | 60 | 2014 |
Passive forensics in image and video using noise features: A review RC Pandey, SK Singh, KK Shukla Digital Investigation 19, 1-28, 2016 | 58 | 2016 |
A comparison among ARIMA, BP-NN, and MOGA-NN for software clone evolution prediction J Pati, B Kumar, D Manjhi, KK Shukla IEEE Access 5, 11841-11851, 2017 | 53 | 2017 |
Real-time task scheduling with fuzzy uncertainty in processing times and deadlines PK Muhuri, KK Shukla Applied soft computing 8 (1), 1-13, 2008 | 42 | 2008 |
Exploring neuro-genetic processing of electronic nose data AK Srivastava, KK Shukla, SK Srivastava Microelectronics Journal 29 (11), 921-931, 1998 | 38 | 1998 |
Robust statistics-based support vector machine and its variants: a survey M Singla, KK Shukla Neural Computing and Applications 32 (15), 11173-11194, 2020 | 37 | 2020 |
A survey of robust optimization based machine learning with special reference to support vector machines M Singla, D Ghosh, KK Shukla International Journal of Machine Learning and Cybernetics 11 (7), 1359-1385, 2020 | 37 | 2020 |
Robust twin support vector regression based on rescaled hinge loss M Singla, D Ghosh, KK Shukla, W Pedrycz Pattern Recognition 105, 107395, 2020 | 36 | 2020 |
Improved multiplication triple generation over rings via RLWE-based AHE D Rathee, T Schneider, KK Shukla International Conference on Cryptology and Network Security, 347-359, 2019 | 36 | 2019 |
Recent trends in nature inspired computation with applications to deep learning V Bharti, B Biswas, KK Shukla 2020 10th International Conference on Cloud Computing, Data Science …, 2020 | 32 | 2020 |