Paper Contents
Abstract
Abstract : This paper synthesizes insights from recent research on 3D object detection and recognition in digital images. The surveyed literature showcases advancements in deep learning architectures, sensor fusion techniques, real-time processing, robustness to occlusion, and domain adaptation. Notably, the integration of point cloud data in deep learning models enhances accuracy, while sensor fusion improves reliability in diverse lighting conditions. Optimized real-time processing, multi-view systems, and domain adaptation methods address specific challenges, contributing to the field's progress. Standard metrics and benchmark evaluations validate the effectiveness of proposed methodologies, highlighting their potential for real-world applications. Keywords : 3D object detection, Recognition, Deep learning, Sensor fusion, Point cloud data.
Copyright
Copyright © 2024 SYEDA MASHOON. This is an open access article distributed under the Creative Commons Attribution License.
