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The following term was not found in PubMed: Jing-Fong
Page 1
Enhancing Geometric Factors in Model Learning and Inference for Object Detection and Instance Segmentation.
Zheng Z, Wang P, Ren D, Liu W, Ye R, Hu Q, Zuo W. Zheng Z, et al. IEEE Trans Cybern. 2022 Aug;52(8):8574-8586. doi: 10.1109/TCYB.2021.3095305. Epub 2022 Jul 19. IEEE Trans Cybern. 2022. PMID: 34437079
In particular, we consider three geometric factors, that is: 1) overlap area; 2) normalized central-point distance; and 3) aspect ratio, which are crucial for measuring bounding-box regression in object detection and instance segmentation. The three geometric factors are then inc …
In particular, we consider three geometric factors, that is: 1) overlap area; 2) normalized central-point distance; and 3) aspect ratio, whi …
Detection of Specific Building in Remote Sensing Images Using a Novel YOLO-S-CIOU Model. Case: Gas Station Identification.
Gao J, Chen Y, Wei Y, Li J. Gao J, et al. Sensors (Basel). 2021 Feb 16;21(4):1375. doi: 10.3390/s21041375. Sensors (Basel). 2021. PMID: 33669229 Free PMC article.
Compared with YOLOv3, YOLO-S-CIOU reduced the parameters' number by 2,510,977 (about 4%) and improved the AP by 2.23% and the F1 score by 0.5%. Moreover, in gas stations detection in Tumshuk City and Yanti City, the recall (R) and precision (P) of YOLO-S-CIOU were 5 …
Compared with YOLOv3, YOLO-S-CIOU reduced the parameters' number by 2,510,977 (about 4%) and improved the AP by 2.23% and the F1 scor …
Helmet-Wearing Tracking Detection Based on StrongSORT.
Li F, Chen Y, Hu M, Luo M, Wang G. Li F, et al. Sensors (Basel). 2023 Feb 3;23(3):1682. doi: 10.3390/s23031682. Sensors (Basel). 2023. PMID: 36772722 Free PMC article.
The experimental results show that the mAP@0.5 of all classes in the YOLOv5s model can reach 95.1% in the validation dataset, mAP@0.5:0.95 is 62.1%, and the precision of wearing helmet is 95.7%. After the box regression loss function was changed from CIOU to Focal-EIOU, th …
The experimental results show that the mAP@0.5 of all classes in the YOLOv5s model can reach 95.1% in the validation dataset, mAP@0.5:0.95 i …
A Lightweight CNN Model Based on GhostNet.
Wang Z, Li T. Wang Z, et al. Comput Intell Neurosci. 2022 Jul 31;2022:8396550. doi: 10.1155/2022/8396550. eCollection 2022. Comput Intell Neurosci. 2022. PMID: 35958795 Free PMC article.
The backbone network draws on the GhostNet design idea, replaces the CSP structure of the FPN and head layers with the GhostBottleNeck module, adds a convolutional attention mechanism module to the backbone network layer, and uses the CIoU loss function to improve the regr …
The backbone network draws on the GhostNet design idea, replaces the CSP structure of the FPN and head layers with the GhostBottleNeck modul …
Face Mask-Wearing Detection Model Based on Loss Function and Attention Mechanism.
Wang Z, Sun W, Zhu Q, Shi P. Wang Z, et al. Comput Intell Neurosci. 2022 Jul 12;2022:2452291. doi: 10.1155/2022/2452291. eCollection 2022. Comput Intell Neurosci. 2022. PMID: 35865498 Free PMC article. Review.
Based on YOLOv5s, we first introduce an attention mechanism in the feature fusion process to improve feature utilization, study the effect of different attention mechanisms (CBAM, SE, and CA) on improving deep network models, and then explore the influence of different bounding b …
Based on YOLOv5s, we first introduce an attention mechanism in the feature fusion process to improve feature utilization, study the effect o …
Helmet Wearing State Detection Based on Improved Yolov5s.
Zhang YJ, Xiao FS, Lu ZM. Zhang YJ, et al. Sensors (Basel). 2022 Dec 14;22(24):9843. doi: 10.3390/s22249843. Sensors (Basel). 2022. PMID: 36560211 Free PMC article.
Firstly, according to the characteristics of the label of the dataset constructed by us, the K-means method is used to redesign the size of the prior box and match it to the corresponding feature layer to increase the accuracy of the feature extraction of the model; secondly, an …
Firstly, according to the characteristics of the label of the dataset constructed by us, the K-means method is used to redesign the size of …
Detection of Farmland Obstacles Based on an Improved YOLOv5s Algorithm by Using CIoU and Anchor Box Scale Clustering.
Xue J, Cheng F, Li Y, Song Y, Mao T. Xue J, et al. Sensors (Basel). 2022 Feb 24;22(5):1790. doi: 10.3390/s22051790. Sensors (Basel). 2022. PMID: 35270935 Free PMC article.
An improved YOLOv5s algorithm based on the K-Means clustering algorithm and CIoU Loss function was proposed to improve detection precision and speed up real-time detection. ...Furthermore, the mAP value of the improved algorithm was increased by 5.80% compared with that of …
An improved YOLOv5s algorithm based on the K-Means clustering algorithm and CIoU Loss function was proposed to improve detection prec …
Improved YOLOv7-based steel surface defect detection algorithm.
Xie Y, Yin B, Han X, Hao Y. Xie Y, et al. Math Biosci Eng. 2024 Jan;21(1):346-368. doi: 10.3934/mbe.2024016. Epub 2022 Dec 13. Math Biosci Eng. 2024. PMID: 38303426 Free article.
Finally, a minimum partial distance intersection over union (MPDIoU) loss function is designed to locate the loss and solve the mismatch problem between the complete intersection over union (CIoU) prediction box and the real box directions. The experimental results show th …
Finally, a minimum partial distance intersection over union (MPDIoU) loss function is designed to locate the loss and solve the mismatch pro …
218 results