What is it about?

The paper presents an advanced model for detecting and tracking objects in adverse weather conditions. It proposes the use of TSM-EFFICIENTDET and JS-KM with Pearson-Retinex to address the challenges posed by weather conditions such as mist, fog, and haze. The model aims to enhance object detection and tracking accuracies under adverse weather conditions by employing innovative techniques and algorithms.

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Why is it important?

The research is important because it addresses a critical challenge in computer vision and surveillance systems. Adverse weather conditions can significantly impact the accuracy of object detection and tracking in video sequences. By proposing an advanced model that specifically targets these challenges, the research aims to improve the reliability and effectiveness of object detection and tracking systems, particularly in real-world scenarios where adverse weather conditions can interfere with traditional methodologies. This has implications for various applications, including surveillance, autonomous vehicles, and robotics, where accurate object detection and tracking are essential.


1. Enhanced Safety and Security: Improved object detection and tracking in adverse weather conditions can enhance safety and security in various domains, such as transportation, surveillance, and public safety, by providing reliable monitoring and detection capabilities even in challenging environmental conditions. 2. Autonomous Systems: The proposed model has the potential to benefit autonomous systems, including self-driving vehicles and unmanned aerial vehicles, by enabling them to maintain accurate object detection and tracking capabilities in adverse weather, thus contributing to safer and more reliable autonomous operations. 3. Disaster Response and Search Operations: In scenarios such as disaster response and search operations, where adverse weather conditions may be prevalent, the ability to detect and track objects effectively despite these challenges can significantly improve the efficiency and effectiveness of such operations. 4. Advancements in Computer Vision: The research contributes to the advancement of computer vision technologies by addressing a specific and significant challenge in object detection and tracking, thereby expanding the capabilities of computer vision systems in real-world, adverse weather conditions.

SRM Institute of Science and Technology

Read the Original

This page is a summary of: Object detection and tracking using TSM-EFFICIENTDET and JS-KM in adverse weather conditions, Journal of Intelligent & Fuzzy Systems, January 2024, IOS Press,
DOI: 10.3233/jifs-233623.
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