Multi-object Detection Method based on YOLO and ResNet Hybrid Networks
This paper proposes a new hybrid network based on YOLO and ResNet (Yolo-resnet) for multi-object detection that integrates ResNet into the feature extraction of the Y OLOv3 framework and detection results demonstrate that the hybrid network is efficient for detecting multi-objects from an image of complex natural scenes.
TL;DR
AI KEY POINTS
ABSTRACT
PAPER
This paper proposes a new hybrid network based on YOLO and ResNet (Yolo-resnet) for multi-object detection that integrates ResNet into the feature extraction of the Y OLOv3 framework and detection results demonstrate that the hybrid network is efficient for detecting multi-objects from an image of complex natural scenes.
Research is provided by Semantic Scholar and AI-generated text may at times produce inaccurate results.
Information provided on this site does not constitute legal, financial, medical, or any other professional advice.
DATA LICENSING
Search and article data is provided under CC BY-NC or ODC-BY and via The Semantic Scholar Open Data Platform. Read more at Kinney, Rodney Michael et al. “The Semantic Scholar Open Data Platform.” ArXiv abs/2301.10140 (2023): n. pag.