Ta-SLOA: Taylor snow leopard optimization with XCovNet-based object classification using vehicle image

Key Points

• The research aims to enhance vehicle object detection accuracy and efficiency using the Ta-SLOA-optimized XCovNet framework.
• Developed the Ta-SLOA optimization algorithm.
• Implemented the XCovNet framework for image classification.
• Tested the framework using vehicle images for accuracy evaluation.
• Significantly improved object detection accuracy compared to previous methods.
• Enhanced detection efficiency suitable for real-time applications.
• Validated effectiveness in the context of intelligent transportation systems.

Abstract