Deep neural network concepts for background subtraction: A systematic review and comparative evaluation
Conventional neural networks have been demonstrated to be a powerful framework for
background subtraction in video acquired by static cameras. Indeed, the well-known Self …
background subtraction in video acquired by static cameras. Indeed, the well-known Self …
Background subtraction in real applications: Challenges, current models and future directions
Computer vision applications based on videos often require the detection of moving objects
in their first step. Background subtraction is then applied in order to separate the background …
in their first step. Background subtraction is then applied in order to separate the background …
An empirical review of deep learning frameworks for change detection: Model design, experimental frameworks, challenges and research needs
M Mandal, SK Vipparthi - IEEE Transactions on Intelligent …, 2021 - ieeexplore.ieee.org
Visual change detection, aiming at segmentation of video frames into foreground and
background regions, is one of the elementary tasks in computer vision and video analytics …
background regions, is one of the elementary tasks in computer vision and video analytics …
Background subtraction for moving object detection: explorations of recent developments and challenges
R Kalsotra, S Arora - The Visual Computer, 2022 - Springer
Background subtraction, although being a very well-established field, has required
significant research efforts to tackle unsolved challenges and to accelerate the progress …
significant research efforts to tackle unsolved challenges and to accelerate the progress …
A survey of moving object detection methods: A practical perspective
X Zhao, G Wang, Z He, H Jiang - Neurocomputing, 2022 - Elsevier
Moving object detection is the foundation of research in many computer vision fields. In
recent decades, a number of detection methods have been proposed. Relevant surveys …
recent decades, a number of detection methods have been proposed. Relevant surveys …
PAGE-Net: interpretable and integrative deep learning for survival analysis using histopathological images and genomic data
J Hao, SC Kosaraju, NZ Tsaku, DH Song… - Pacific Symposium on …, 2019 - World Scientific
The integration of multi-modal data, such as histopathological images and genomic data, is
essential for understanding cancer heterogeneity and complexity for personalized …
essential for understanding cancer heterogeneity and complexity for personalized …
Deep learning-based moving object segmentation: Recent progress and research prospects
R Jiang, R Zhu, H Su, Y Li, Y Xie, W Zou - Machine Intelligence Research, 2023 - Springer
Moving object segmentation (MOS), aiming at segmenting moving objects from video
frames, is an important and challenging task in computer vision and with various …
frames, is an important and challenging task in computer vision and with various …
Video foreground extraction using multi-view receptive field and encoder–decoder DCNN for traffic and surveillance applications
The automatic detection of foreground (FG) objects in videos is a demanding area of
computer vision, with essential applications in video-based traffic analysis and surveillance …
computer vision, with essential applications in video-based traffic analysis and surveillance …
Modified ResNet-152 network with hybrid pyramidal pooling for local change detection
In this article, we put forth a unique attempt to detect the local changes in challenging video
scenes by exploring the capabilities of an encoder-decoder type network that employs a …
scenes by exploring the capabilities of an encoder-decoder type network that employs a …
[PDF][PDF] An end-to-end deep learning approach for simultaneous background modeling and subtraction.
Background subtraction is an active research topic due to its great utility on many video
analysis applications. In this work, a new approach for background subtraction employing an …
analysis applications. In this work, a new approach for background subtraction employing an …