Object Detection and Tracking
원문 초록
Efficient and accurate object detection is an important topic in the development of computer vision systems. With the advent of deep learning techniques, the accuracy of object detection has increased significantly. The project aims to integrate a modern technique for object detection with the aim of achieving high accuracy with real-time performance. The reliance on other computer vision algorithms in many object identification systems, which results in poor and ineffective performance, is a significant obstacle. In this research, we solve the end-to-end object detection problem entirely using deep learning techniques. The network is trained using the most difficult publicly available dataset, which is used for an annual item detection challenge. Applications that need object detection can benefit the system's quick and precise finding.
함께 살펴볼 논문
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Towards Reliable Detection of Empty Space: Conditional Marked Point Processes for Object Detection
Multiple Object Stitching for Unsupervised Representation Learning
Domain Randomization for Object Detection in Manufacturing Applications using Synthetic Data: A Comprehensive Study
Edge-Enabled Collaborative Object Detection for Real-Time Multi-Vehicle Perception
Multispectral Detection Transformer with Infrared-Centric Sensor Fusion
A Real-Time System for Egocentric Hand-Object Interaction Detection in Industrial Domains
토론
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