K K Shukla
K K Shukla
Professor of Computer Engineering, IIT (BHU)
Verified email at - Homepage
Cited by
Cited by
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
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
Neuro-genetic prediction of software development effort
KK Shukla
Information and Software Technology 42 (10), 701-713, 2000
Efficient algorithms for discrete wavelet transform: with applications to denoising and fuzzy inference systems
KK Shukla, AK Tiwari
Springer Science & Business Media, 2013
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
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
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
Passive copy-move forgery detection in videos
RC Pandey, SK Singh, KK Shukla
2014 International conference on computer and communication technology …, 2014
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
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
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
Passive forensics in image and video using noise features: A review
RC Pandey, SK Singh, KK Shukla
Digital Investigation 19, 1-28, 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
Real-time task scheduling with fuzzy uncertainty in processing times and deadlines
PK Muhuri, KK Shukla
Applied soft computing 8 (1), 1-13, 2008
Evolution in Computational Intelligence
V Bhateja, SL Peng, SC Satapathy, YD Zhang
Springer, 2021
Exploring neuro-genetic processing of electronic nose data
AK Srivastava, KK Shukla, SK Srivastava
Microelectronics Journal 29 (11), 921-931, 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
Robust twin support vector regression based on rescaled hinge loss
M Singla, D Ghosh, KK Shukla, W Pedrycz
Pattern Recognition 105, 107395, 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
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
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