UNIQUE: Unsupervised Image Quality Estimation. - Dogancan Temel; Mohit Prabhushankar; Ghassan AlRegib (IEEE Signal Process. Lett., 2016)

Generating adaptive and robust filter sets using an unsupervised learning framework. - Mohit Prabhushankar; Dogancan Temel; Ghassan AlRegib (ICIP, 2017)

MS-UNIQUE: Multi-model and Sharpness-weighted Unsupervised Image Quality Estimation. - Mohit Prabhushankar; Dogancan Temel; Ghassan AlRegib (IQSP, 2017)

CURE-TSR: Challenging Unreal and Real Environments for Traffic Sign Recognition. - Dogancan Temel; Gukyeong Kwon; Mohit Prabhushankar; Ghassan AlRegib (CoRR, 2017)

Semantically Interpretable and Controllable Filter Sets. - Mohit Prabhushankar; Gukyeong Kwon; Dogancan Temel; Ghassan AlRegib (ICIP, 2018)

Distorted Representation Space Characterization Through Backpropagated Gradients. - Gukyeong Kwon; Mohit Prabhushankar; Dogancan Temel; Ghassan AlRegib (ICIP, 2019)

Backpropagated Gradient Representations for Anomaly Detection. - Gukyeong Kwon; Mohit Prabhushankar; Dogancan Temel; Ghassan AlRegib (ECCV (21), 2020)

Novelty Detection Through Model-Based Characterization of Neural Networks. - Gukyeong Kwon; Mohit Prabhushankar; Dogancan Temel; Ghassan AlRegib (ICIP, 2020)

Contrastive Explanations In Neural Networks. - Mohit Prabhushankar; Gukyeong Kwon; Dogancan Temel; Ghassan AlRegib (ICIP, 2020)

Implicit Saliency In Deep Neural Networks. - Yutong Sun; Mohit Prabhushankar; Ghassan AlRegib (ICIP, 2020)

Extracting Causal Visual Features For Limited Label Classification. - Mohit Prabhushankar; Ghassan AlRegib (ICIP, 2021)

Contrastive Reasoning in Neural Networks. - Mohit Prabhushankar; Ghassan AlRegib (CoRR, 2021)

CURE-TSR: Challenging Unreal and Real Environments for Traffic Sign Recognition. - Dogancan Temel; Gukyeong Kwon; Mohit Prabhushankar; Ghassan AlRegib (IEEE DataPort, 2021)

Forgetful Active Learning with Switch Events: Efficient Sampling for Out-of-Distribution Data. - Ryan Benkert; Mohit Prabhushankar; Ghassan AlRegib (ICIP, 2022)

Gradient-Based Severity Labeling for Biomarker Classification in Oct. - Kiran Kokilepersaud; Mohit Prabhushankar; Ghassan AlRegib; Stephanie Trejo Corona; Charles C. Wykoff (ICIP, 2022)

Introspective Learning : A Two-Stage approach for Inference in Neural Networks. - Mohit Prabhushankar; Ghassan AlRegib (NeurIPS, 2022)

OLIVES Dataset: Ophthalmic Labels for Investigating Visual Eye Semantics. - Mohit Prabhushankar; Kiran Kokilepersaud; Yash-Yee Logan; Stephanie Trejo Corona; Ghassan AlRegib; Charles C. Wykoff (NeurIPS, 2022)

Explanatory Paradigms in Neural Networks. - Ghassan AlRegib; Mohit Prabhushankar (CoRR, 2022)

Volumetric Supervised Contrastive Learning for Seismic Semantic Segmentation. - Kiran Kokilepersaud; Mohit Prabhushankar; Ghassan AlRegib (CoRR, 2022)

Gradient-Based Adversarial and Out-of-Distribution Detection. - Jinsol Lee; Mohit Prabhushankar; Ghassan AlRegib (CoRR, 2022)

Clinical Contrastive Learning for Biomarker Detection. - Kiran Kokilepersaud; Mohit Prabhushankar; Ghassan AlRegib (CoRR, 2022)

On the Ramifications of Human Label Uncertainty. - Chen Zhou; Mohit Prabhushankar; Ghassan AlRegib (CoRR, 2022)

Explanatory Paradigms in Neural Networks: Towards relevant and contextual explanations. - Ghassan AlRegib; Mohit Prabhushankar (IEEE Signal Process. Mag., 2022)

Clinical Trial Active Learning. - Zoe Fowler; Kiran Premdat Kokilepersaud; Mohit Prabhushankar; Ghassan Alregib (BCB, 2023)

FOCAL: A Cost-Aware Video Dataset for Active Learning. - Kiran Kokilepersaud; Yash-Yee Logan; Ryan Benkert; Chen Zhou; Mohit Prabhushankar; Ghassan AlRegib; Enrique Corona; Kunjan Singh; Mostafa Parchami (IEEE Big Data, 2023)

Probing the Purview of Neural Networks via Gradient Analysis. - Jinsol Lee; Charlie Lehman; Mohit Prabhushankar; Ghassan AlRegib (IEEE Access, 2023)

Stochastic Surprisal: An inferential measurement of Free Energy in Neural Networks. - Mohit Prabhushankar; Ghassan AlRegib (CoRR, 2023)

Exploiting the Distortion-Semantic Interaction in Fisheye Data. - Kiran Kokilepersaud; Mohit Prabhushankar; Yavuz Yarici; Ghassan AlRegib; Armin Parchami (CoRR, 2023)

Contrastive Reasoning in Neural Networks. - Mohit Prabhushankar (2023)

Clinically Labeled Contrastive Learning for OCT Biomarker Classification. - Kiran Kokilepersaud; Stephanie Trejo Corona; Mohit Prabhushankar; Ghassan AlRegib; Charles C. Wykoff (IEEE J. Biomed. Health Informatics, 2023)

Understanding and Leveraging the Learning Phases of Neural Networks. - Johannes Schneider; Mohit Prabhushankar (AAAI, 2024)

Targeting Negative Flips in Active Learning using Validation Sets. - Ryan Benkert; Mohit Prabhushankar; Ghassan AlRegib (IEEE Big Data, 2024)

Benchmarking Human and Automated Prompting in the Segment Anything Model. - Jorge Quesada; Zoe Fowler; Mohammad Alotaibi; Mohit Prabhushankar; Ghassan AlRegib (IEEE Big Data, 2024)

PointPrompt: A Multi-modal Prompting Dataset for Segment Anything Model. - Jorge Quesada; Mohammad Alotaibi; Mohit Prabhushankar; Ghassan AlRegib (CVPR Workshops, 2024)

Are Objective Explanatory Evaluation Metrics Trustworthy? An Adversarial Analysis. - Prithwijit Chowdhury; Mohit Prabhushankar; Ghassan AlRegib; Mohamed Deriche 001 (ICIP, 2024)

Taxes are All You Need: Integration Of Taxonomical Hierarchy Relationships Into the Contrastive Loss. - Kiran Kokilepersaud; Yavuz Yarici; Mohit Prabhushankar; Ghassan AlRegib (ICIP, 2024)

Intelligent Multi-View Test Time Augmentation. - Efe Ozturk; Mohit Prabhushankar; Ghassan AlRegib (ICIP, 2024)

Explaining Representation Learning With Perceptual Components. - Yavuz Yarici; Kiran Kokilepersaud; Mohit Prabhushankar; Ghassan AlRegib (ICIP, 2024)

Transitional Uncertainty with Layered Intermediate Predictions. - Ryan Benkert; Mohit Prabhushankar; Ghassan AlRegib (ICML, 2024)

Counterfactual Gradients-based Quantification of Prediction Trust in Neural Networks. - Mohit Prabhushankar; Ghassan AlRegib (MIPR, 2024)

CRACKS: Crowdsourcing Resources for Analysis and Categorization of Key Subsurface faults. - Mohit Prabhushankar; Kiran Kokilepersaud; Jorge Quesada; Yavuz Yarici; Chen Zhou; Mohammad Alotaibi; Ghassan AlRegib (Zenodo, 2024)

PointPrompt: A Multi-modal Prompting Dataset for Segment Anything Model. - Jorge Quesada; Mohammad Alotaibi; Mohit Prabhushankar; Ghassan AlRegib (Zenodo, 2024)

Perceptual Quality-based Model Training under Annotator Label Uncertainty. - Chen Zhou; Mohit Prabhushankar; Ghassan AlRegib (CoRR, 2024)

CRACKS: Crowdsourcing Resources for Analysis and Categorization of Key Subsurface faults. - Mohit Prabhushankar; Kiran Kokilepersaud; Jorge Quesada; Yavuz Yarici; Chen Zhou; Mohammad Alotaibi; Ghassan AlRegib; Ahmad Mustafa 002; Yusufjon Kumakov (CoRR, 2024)

Effective Data Selection for Seismic Interpretation Through Disagreement. - Ryan Benkert; Mohit Prabhushankar; Ghassan AlRegib (IEEE Trans. Geosci. Remote. Sens., 2024)

Gaussian Switch Sampling: A Second-Order Approach to Active Learning. - Ryan Benkert; Mohit Prabhushankar; Ghassan AlRegib; Armin Pacharmi; Enrique Corona (IEEE Trans. Artif. Intell., 2024)

SegFaults in the Earth. - Ghassan AlRegib; Mohit Prabhushankar; Chen Zhou; Prithwijit Chowdhury; Jorge Quesada (Zenodo, 2024)

PointPrompt: A Multi-modal Prompting Dataset for Segment Anything Model. - Jorge Quesada; Mohammad Alotaibi; Mohit Prabhushankar; Ghassan AlRegib (Zenodo, 2024)

DARai: Daily Activity Recordings for AI and ML aplications. - Ghazal Kaviani; Yavuz Yarici; Mohit Prabhushankar; Ghassan AlRegib; Mashhour Solh; Ameya Patil (IEEE DataPort, 2024)

CRACKS: Crowdsourcing Resources for Analysis and Categorization of Key Subsurface faults. - Mohit Prabhushankar; Kiran Kokilepersaud; Jorge Quesada; Yavuz Yarici; Chen Zhou; Mohammad Alotaibi; Ghassan AlRegib (Zenodo, 2024)

PointPrompt: A Visual Prompting Dataset based on the Segment Anything Model. - Jorge Quesada; Zoe Fowler; Mohammad Alotaibi; Mohit Prabhushankar; Ghassan AlRegib (Zenodo, 2024)

Ophthalmic Biomarker Detection: Highlights From the IEEE Video and Image Processing Cup 2023 Student Competition [SP Competitions]. - Ghassan AlRegib; Mohit Prabhushankar; Kiran Kokilepersaud; Prithwijit Chowdhury; Zoe Fowler; Stephanie Trejo Corona; Lucas A. Thomaz; Angshul Majumdar (IEEE Signal Process. Mag., 2024)

HEX: Hierarchical Emergence Exploitation in Self-Supervised Algorithms. - Kiran Kokilepersaud; Seulgi Kim; Mohit Prabhushankar; Ghassan AlRegib (WACV, 2025)

VOICE: Variance of Induced Contrastive Explanations to Quantify Uncertainty in Neural Network Interpretability. - Mohit Prabhushankar; Ghassan AlRegib (IEEE J. Sel. Top. Signal Process., 2025)

Hierarchical and Multimodal Data for Daily Activity Understanding. - Ghazal Kaviani; Yavuz Yarici; Seulgi Kim; Mohit Prabhushankar; Ghassan AlRegib; Mashhour Solh; Ameya Patil (CoRR, 2025)

A Large-scale Benchmark on Geological Fault Delineation Models: Domain Shift, Training Dynamics, Generalizability, Evaluation and Inferential Behavior. - Jorge Quesada; Chen Zhou; Prithwijit Chowdhury; Mohammad Alotaibi; Ahmad Mustafa 002; Yusufjon Kumakov; Mohit Prabhushankar; Ghassan AlRegib (CoRR, 2025)

AdaDim: Dimensionality Adaptation for SSL Representational Dynamics. - Kiran Kokilepersaud; Mohit Prabhushankar; Ghassan AlRegib (CoRR, 2025)

Multi-level and Multi-modal Action Anticipation. - Seulgi Kim; Ghazal Kaviani; Mohit Prabhushankar; Ghassan AlRegib (CoRR, 2025)

Subject Invariant Contrastive Learning for Human Activity Recognition. - Yavuz Yarici; Kiran Kokilepersaud; Mohit Prabhushankar; Ghassan AlRegib (CoRR, 2025)