By combining the analysis from both the LRCN model and the Motionless Object Detection Algorithm, our system can effectively identify and annotate suspicious activities in the video …

In this paper, we employ five CNN architectures: ResNet50, VGG16, 2D-CNN, Transfer Learning[3] using CNN (VGG16 and ResNet50). The primary goal of this paper is to detect …

Dec 16, 2022 · Nowadays machine learning (ML)- and deep learning (DL)-based pre-incident warning alarm systems could be adapted to monitor suspicious activity. Suspicious activity …

This paper provides a Deep learning algorithm of suspicious activity detection. This algorithm displays which frame and part of unusual activity, which aids in the quicker assessment of that …

Server-side application is linked to an IP camera which detects suspicious activity, determines crowd level at the entrance of any public/private place by making use of Social Force Model …

suspicious activity detection is to train models on vast amounts of labeled data, allowing them to learn intricate patterns and deviations indicative of suspicious behavior. A CNN can learn …

suspicious activity is used in applications including video surveillance, animal tracking and behavior understanding, sign language detection, advanced human-computer interaction, and …

In this paper, a innovative neural network is proposed for anomaly detection which is also labeled as AnomalyNet by deeply accomplishing feature learning, sparse representation as well as …

This research introduces a novel solution that leverages the SSAAlgorithm to enhance the capabilities ofa deep CNN classifier, enabling more accurate and reliable identification of …

The main motivation of this suspicious activity detection is to prevent various suspicious activities such as terrorism, theft cases, accidents, vandalism, fighting, crime and other suspicious …