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Deep neural network concepts for background subtraction:A systematic review and comparative evaluation

Neural networks, 2019-09, Vol.117, p.8-66

2019

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Epistemic Uncertainty in Artificial Intelligence: First International Workshop, Epi UAI 2023, Pittsburgh, PA, USA, August 4, 2023, Revised Selected Papers

2024th edition, 2024

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Unsupervised deep context prediction for background estimation and foreground segmentation

Machine vision and applications, 2019-04, Vol.30 (3), p.375-395

2019

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Unsupervised moving object segmentation using background subtraction and optimal adversarial noise sample search

Pattern recognition, 2022-09, Vol.129, p.108719, Article 108719

2022

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Unsupervised Moving Object Detection in Complex Scenes Using Adversarial Regularizations

IEEE transactions on multimedia, 2021, Vol.23, p.2005-2018

2021

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Epistemic Uncertainty in Artificial Intelligence: First International Workshop, Epi UAI 2023, Pittsburgh, PA, USA, August 4, 2023, Revised Selected Papers

2024

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Moving objects segmentation using generative adversarial modeling

Neurocomputing (Amsterdam), 2022-09, Vol.506, p.240-251

2022

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The Emerging Field of Graph Signal Processing for Moving Object Segmentation

Frontiers of Computer Vision, p.31-45

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Dynamic Background Subtraction Using Least Square Adversarial Learning

2020 IEEE International Conference on Image Processing (ICIP), 2020, p.3204-3208

2020

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Local binary pattern variants-based adaptive texture features analysis for posed and nonposed facial expression recognition

Journal of electronic imaging, 2017-09, Vol.26 (5), p.1

2017

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Towards Understanding the Interplay of Generative Artificial Intelligence and the Internet

Epistemic Uncertainty in Artificial Intelligence, 2024, Vol.14523, p.59-73

2024

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Unsupervised Adversarial Learning for Dynamic Background Modeling

Frontiers of Computer Vision, p.248-261

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Bag of Policies for Distributional Deep Exploration

Epistemic Uncertainty in Artificial Intelligence, 2024, Vol.14523, p.28-43

2024

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Deep Learning and MCMC with aggVAE for Shifting Administrative Boundaries: Mapping Malaria Prevalence in Kenya

Epistemic Uncertainty in Artificial Intelligence, 2024, Vol.14523, p.13-27

2024

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Semantic Attribution for Explainable Uncertainty Quantification

Epistemic Uncertainty in Artificial Intelligence, 2024, Vol.14523, p.101-112

2024

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Defensive Perception: Estimation and Monitoring of Neural Network Performance Under Deployment

Epistemic Uncertainty in Artificial Intelligence, 2024, Vol.14523, p.44-58

2024

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Towards Offline Reinforcement Learning with Pessimistic Value Priors

Epistemic Uncertainty in Artificial Intelligence, 2024, Vol.14523, p.89-100

2024

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A Novel Bayes' Theorem for Upper Probabilities

Epistemic Uncertainty in Artificial Intelligence, 2024, Vol.14523, p.1-12

2024

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Optimizing Brain Tumor Classification: A Comprehensive Study on Transfer Learning and Imbalance Handling in Deep Learning Models

Epistemic Uncertainty in Artificial Intelligence, 2024, Vol.14523, p.74-88

2024

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Moving Object Detection on RGB-D Videos Using Graph Regularized Spatiotemporal RPCA

New Trends in Image Analysis and Processing – ICIAP 2017, p.230-241

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Deep Matting for AR Based Interior Design

Frontiers of Computer Vision, p.31-42

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Sustainability In Education And Research In Public Sector Universities Of AJ&K

Webology, 2022-01, Vol.19 (3), p.1408-1424

2022

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Efficacy of transverses abdomens plane (tap) block for post-operative pain in patients undergoing total abdominal hysterectomy

NeuroQuantology, 2022-01, Vol.20 (16), p.686

2022

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THE INTRATHECAL DEXMEDETOMEDINE EFFECT AS HYPERBARIC BUPIVACAIN ADJUVANT IN THE ELECTIVE C-SECTION

NeuroQuantology, 2022-01, Vol.20 (15), p.5036

2022

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Background/Foreground Separation: Guided Attention based Adversarial Modeling (GAAM) versus Robust Subspace Learning Methods

2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), 2021, p.181-188

2021

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Deep neural network concepts for background subtraction:A systematic review and comparative evaluation

Epistemic Uncertainty in Artificial Intelligence: First International Workshop, Epi UAI 2023, Pittsburgh, PA, USA, August 4, 2023, Revised Selected Papers

Unsupervised deep context prediction for background estimation and foreground segmentation

Unsupervised moving object segmentation using background subtraction and optimal adversarial noise sample search

Unsupervised Moving Object Detection in Complex Scenes Using Adversarial Regularizations

Epistemic Uncertainty in Artificial Intelligence: First International Workshop, Epi UAI 2023, Pittsburgh, PA, USA, August 4, 2023, Revised Selected Papers

Moving objects segmentation using generative adversarial modeling

The Emerging Field of Graph Signal Processing for Moving Object Segmentation

Dynamic Background Subtraction Using Least Square Adversarial Learning

Local binary pattern variants-based adaptive texture features analysis for posed and nonposed facial expression recognition

Towards Understanding the Interplay of Generative Artificial Intelligence and the Internet

Unsupervised Adversarial Learning for Dynamic Background Modeling

Bag of Policies for Distributional Deep Exploration

Deep Learning and MCMC with aggVAE for Shifting Administrative Boundaries: Mapping Malaria Prevalence in Kenya

Semantic Attribution for Explainable Uncertainty Quantification

Defensive Perception: Estimation and Monitoring of Neural Network Performance Under Deployment

Towards Offline Reinforcement Learning with Pessimistic Value Priors

A Novel Bayes' Theorem for Upper Probabilities

Optimizing Brain Tumor Classification: A Comprehensive Study on Transfer Learning and Imbalance Handling in Deep Learning Models

Moving Object Detection on RGB-D Videos Using Graph Regularized Spatiotemporal RPCA

Deep Matting for AR Based Interior Design

Sustainability In Education And Research In Public Sector Universities Of AJ&K

Efficacy of transverses abdomens plane (tap) block for post-operative pain in patients undergoing total abdominal hysterectomy

THE INTRATHECAL DEXMEDETOMEDINE EFFECT AS HYPERBARIC BUPIVACAIN ADJUVANT IN THE ELECTIVE C-SECTION

Background/Foreground Separation: Guided Attention based Adversarial Modeling (GAAM) versus Robust Subspace Learning Methods

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