Distributed quadratic programming solver for kernel SVM using genetic algorithm. - Dinesh Singh 001; C. Krishna Mohan (CEC, 2016)

Spontaneous Facial Expression Recognition: A Part Based Approach. - Nazil Perveen; Dinesh Singh 001; C. Krishna Mohan (ICMLA, 2016)

Visual Big Data Analytics for Traffic Monitoring in Smart City. - Dinesh Singh 001; Chalavadi Vishnu; C. Krishna Mohan (ICMLA, 2016)

Automatic detection of bike-riders without helmet using surveillance videos in real-time. - Kunal Dahiya; Dinesh Singh 001; C. Krishna Mohan (IJCNN, 2016)

Collaborative IDS Framework for Cloud. - Dinesh Singh 001; Dhiren Patel; Bhavesh Borisaniya; Chirag Modi 001 (Int. J. Netw. Secur., 2016)

Detection of motorcyclists without helmet in videos using convolutional neural network. - Chalavadi Vishnu; Dinesh Singh 001; C. Krishna Mohan; Ch. Sobhan Babu (IJCNN, 2017)

Graph formulation of video activities for abnormal activity recognition. - Dinesh Singh 001; C. Krishna Mohan (Pattern Recognit., 2017)

DiP-SVM : Distribution Preserving Kernel Support Vector Machine for Big Data. - Dinesh Singh 001; Debaditya Roy; C. Krishna Mohan (IEEE Trans. Big Data, 2017)

Projection-SVM: Distributed Kernel Support Vector Machine for Big Data using Subspace Partitioning. - Dinesh Singh 001; C. Krishna Mohan (IEEE BigData, 2018)

Fast-BoW: Scaling Bag-of-Visual-Words Generation. - Dinesh Singh 001; Abhijeet Bhure; Sumit Mamtani; C. Krishna Mohan (BMVC, 2018)

Deep Spatio-Temporal Representation for Detection of Road Accidents Using Stacked Autoencoder. - Dinesh Singh 001; Chalavadi Krishna Mohan (IEEE Trans. Intell. Transp. Syst., 2019)

Real-Time Detection of Motorcyclist without Helmet using Cascade of CNNs on Edge-device. - Dinesh Singh 001; Chalavadi Vishnu; C. Krishna Mohan (ITSC, 2020)

GraphLIME: Local Interpretable Model Explanations for Graph Neural Networks. - Qiang Huang; Makoto Yamada; Yuan Tian 016; Dinesh Singh 001; Dawei Yin; Yi Chang 001 (CoRR, 2020)

FsNet: Feature Selection Network on High-dimensional Biological Data. - Dinesh Singh 001; Makoto Yamada (CoRR, 2020)

Nys-Curve: Nyström-Approximated Curvature for Stochastic Optimization. - Hardik Tankaria; Dinesh Singh 001; Makoto Yamada (CoRR, 2021)

Graph Representation for Weakly-Supervised Spatio-Temporal Action Detection. - Dinesh Singh 001 (IJCNN, 2023)

FsNet: Feature Selection Network on High-dimensional Biological Data. - Dinesh Singh 001; Héctor Climente-González; Mathis Petrovich; Eiryo Kawakami; Makoto Yamada (IJCNN, 2023)

GraphLIME: Local Interpretable Model Explanations for Graph Neural Networks. - Qiang Huang; Makoto Yamada; Yuan Tian 016; Dinesh Singh 001; Yi Chang 001 (IEEE Trans. Knowl. Data Eng., 2023)

Tackling Data Heterogeneity in Federated Learning through Global Density Estimation. - Sagnik Ghosh; Avinash Kushwaha; Dinesh Singh 001 (IEEE Big Data, 2024)

Predicting Stress among Students via Psychometric Assessments and Machine Learning. - Sagnik Ghosh; Kirti Tripathi; Ankita Garg; Dinesh Singh 001; Amit Prasad; Arnav Bhavsar; Varun Dutt (PETRA, 2024)

Unified Anomaly Detection methods on Edge Device using Knowledge Distillation and Quantization. - Sushovan Jena; Arya Pulkit; Kajal Singh; Anoushka Banerjee; Sharad Joshi; Ananth Ganesh; Dinesh Singh 001; Arnav Bhavsar (CoRR, 2024)

Cross-Domain Identity Representation for Skull to Face Matching with Benchmark DataSet. - Ravi Shankar Prasad; Dinesh Singh 001 (CoRR, 2025)

Exp-Graph: How Connections Learn Facial Attributes in Graph-based Expression Recognition. - Nandani Sharma; Dinesh Singh 001 (CoRR, 2025)