[HTML][HTML] An explainable and efficient deep learning framework for video anomaly detection
Deep learning-based video anomaly detection methods have drawn significant attention in
the past few years due to their superior performance. However, almost all the leading …
the past few years due to their superior performance. However, almost all the leading …
[HTML][HTML] Wildfire and smoke detection using staged YOLO model and ensemble CNN
One of the most expensive and fatal natural disasters in the world is forest fires. For this
reason, early discovery of forest fires helps minimize mortality and harm to ecosystems and …
reason, early discovery of forest fires helps minimize mortality and harm to ecosystems and …
Video hand gestures recognition using depth camera and lightweight cnn
Hand gestures are a well-known and intuitive method of human-computer interaction. The
majority of the research has concentrated on hand gesture recognition from the RGB …
majority of the research has concentrated on hand gesture recognition from the RGB …
[HTML][HTML] Forest fire smoke detection based on deep learning approaches and unmanned aerial vehicle images
SY Kim, A Muminov - Sensors, 2023 - mdpi.com
Wildfire poses a significant threat and is considered a severe natural disaster, which
endangers forest resources, wildlife, and human livelihoods. In recent times, there has been …
endangers forest resources, wildlife, and human livelihoods. In recent times, there has been …
Anomaly detection in surveillance videos: a thematic taxonomy of deep models, review and performance analysis
The task of anomaly detection has recently gained much attention in the field of visual
surveillance. Video surveillance data is often available in large quantities, but manual …
surveillance. Video surveillance data is often available in large quantities, but manual …
Bi-READ: Bi-Residual AutoEncoder based feature enhancement for video anomaly detection
R Kommanduri, M Ghorai - Journal of Visual Communication and Image …, 2023 - Elsevier
Video anomaly detection (VAD) refers to identifying abnormal events in the surveillance
video. Typically, reconstruction based video anomaly detection techniques employ …
video. Typically, reconstruction based video anomaly detection techniques employ …
[HTML][HTML] Deep crowd anomaly detection by fusing reconstruction and prediction networks
Abnormal event detection is one of the most challenging tasks in computer vision. Many
existing deep anomaly detection models are based on reconstruction errors, where the …
existing deep anomaly detection models are based on reconstruction errors, where the …
Visual crowd analysis: Open research problems
Over the last decade, there has been a remarkable surge in interest in automated crowd
monitoring within the computer vision community. Modern deep‐learning approaches have …
monitoring within the computer vision community. Modern deep‐learning approaches have …
Deep Crowd Anomaly Detection: State-of-the-Art, Challenges, and Future Research Directions
MH Sharif, L Jiao, CW Omlin - arXiv preprint arXiv:2210.13927, 2022 - arxiv.org
Crowd anomaly detection is one of the most popular topics in computer vision in the context
of smart cities. A plethora of deep learning methods have been proposed that generally …
of smart cities. A plethora of deep learning methods have been proposed that generally …
[HTML][HTML] Selecting post-processing schemes for accurate detection of small objects in low-resolution wide-area aerial imagery
In low-resolution wide-area aerial imagery, object detection algorithms are categorized as
feature extraction and machine learning approaches, where the former often requires a post …
feature extraction and machine learning approaches, where the former often requires a post …