Results 11 to 20 of about 487,056 (216)
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015 State-of-the-art object detection networks depend on region proposal algorithms to hypothesize object locations. Advances like SPPnet and Fast R-CNN have reduced the running time of these detection networks, exposing region proposal computation as a ...
Girshick, Ross +3 more
core +2 more sources
DeFRCN: Decoupled Faster R-CNN for Few-Shot Object Detection [PDF]
IEEE International Conference on Computer Vision, 2021 Few-shot object detection, which aims at detecting novel objects rapidly from extremely few annotated examples of previously unseen classes, has attracted significant research interest in the community. Most existing approaches employ the Faster R-CNN as
Limeng Qiao +5 more
semanticscholar +1 more source
The Role of Faster R-CNN Algorithm in the Internet of Things to Detect Mask Wearing: The Endemic Preparations [PDF]
International Journal of Electronics and Telecommunications, 2023 Faster R-CNN is an algorithm development that continuously starts from CNN then R-CNN and Faster R-CNN. The development of the algorithm is needed to test whether the heuristic algorithm has optimal provisions.
Marah Doly Nasution +4 more
doaj +1 more source
An Overview of Object Detection and Tracking Algorithms
Engineering Proceedings, 2023 With the development of information technology, the vision-based detection and tracking of moving objects is gradually penetrating into all aspects of people’s lives, and its importance is becoming more prominent, attracting more and more scientists and ...
Kehao Du, Alexander Bobkov
doaj +1 more source
Innovative Region Convolutional Neural Network Algorithm for Object Identification
Journal of Open Innovation: Technology, Market and Complexity, 2022 : Object identification is a part of the field of computer science, namely, image processing, whose research continues to innovate. Object identification describes an object based on the main characteristics of the object.
Yurika Permanasari +3 more
doaj +1 more source
Effectiveness of traditional augmentation methods for rebar counting using UAV imagery with Faster R-CNN and YOLOv10-based transformer architectures. [PDF]
Sci RepAccurate inspection of Reinforced Concrete (RC) structures requires precise rebar counting. Although deep-learning object detectors can extract this information from drone imagery, their effectiveness depends on large, diverse, and well-labeled datasets.
Wang S.
europepmc +2 more sources
Few-Shot Adaptive Faster R-CNN [PDF]
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019 Accepted at CVPR ...
Wang, Tao +3 more
openaire +2 more sources
Domain Adaptive Faster R-CNN for Object Detection in the Wild [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 Object detection typically assumes that training and test data are drawn from an identical distribution, which, however, does not always hold in practice. Such a distribution mismatch will lead to a significant performance drop.
Yuhua Chen +4 more
semanticscholar +1 more source
Local keypoint-based Faster R-CNN [PDF]
Applied Intelligence, 2020 Region-based Convolutional Neural Network (R-CNN) detectors have achieved state-of-the-art results on various challenging benchmarks. Although R-CNN has achieved high detection performance, the research of local information in producing candidates is insufficient.
Ding, Xintao +5 more
openaire +2 more sources
Is Faster R-CNN Doing Well for Pedestrian Detection? [PDF]
European Conference on Computer Vision, 2016 Detecting pedestrian has been arguably addressed as a special topic beyond general object detection. Although recent deep learning object detectors such as Fast/Faster R-CNN have shown excellent performance for general object detection, they have limited
Liliang Zhang +3 more
semanticscholar +1 more source