Detecting and Tracking Objects in Challenging Weather Conditions Using Advanced Models

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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.

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