Cargando…
Object Detection Based on Faster R-CNN Algorithm with Skip Pooling and Fusion of Contextual Information
Deep learning is currently the mainstream method of object detection. Faster region-based convolutional neural network (Faster R-CNN) has a pivotal position in deep learning. It has impressive detection effects in ordinary scenes. However, under special conditions, there can still be unsatisfactory...
Autores principales: | Xiao, Yi, Wang, Xinqing, Zhang, Peng, Meng, Fanjie, Shao, Faming |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7582940/ https://www.ncbi.nlm.nih.gov/pubmed/32992739 http://dx.doi.org/10.3390/s20195490 |
Ejemplares similares
-
Improved Faster R-CNN Traffic Sign Detection Based on a Second Region of Interest and Highly Possible Regions Proposal Network
por: Shao, Faming, et al.
Publicado: (2019) -
Spatial–Semantic and Temporal Attention Mechanism-Based Online Multi-Object Tracking
por: Meng, Fanjie, et al.
Publicado: (2020) -
Pneumonia Detection Using an Improved Algorithm Based on Faster R-CNN
por: Yao, Shangjie, et al.
Publicado: (2021) -
Real-Time Water Surface Object Detection Based on Improved Faster R-CNN
por: Zhang, Lili, et al.
Publicado: (2019) -
Improved Faster R-CNN Based Surface Defect Detection Algorithm for Plates
por: Xia, Baizhan, et al.
Publicado: (2022)