A Model for Real-Time Traffic Signs Recognition Based on the YOLO Algorithm — A Case Study Using Vietnamese Traffic Signs Tran et al, 2019, published in: Future Data and Security Engineering D. Zhou et al., “IoU Loss for 2D/3D Object Detection,” 2019 International Conference on 3D Vi...
A Model for Real-Time Traffic Signs Recognition Based on the YOLO Algorithm — A Case Study Using Vietnamese Traffic Signs Tran et al, 2019, published in: Future Data and Security Engineering D. Zhou et al., “IoU Loss for 2D/3D Object Detection,” 2019 International Conference on 3D Vi...
A Model for Real-Time Traffic Signs Recognition Based on the YOLO Algorithm — A Case Study Using Vietnamese Traffic Signs Tran et al, 2019, published in: Future Data and Security Engineering D. Zhou et al., “IoU Loss for 2D/3D Object Detection,” 2019 International Conference on 3D Vi...
A Model for Real-Time Traffic Signs Recognition Based on the YOLO Algorithm — A Case Study Using Vietnamese Traffic Signs Tran et al, 2019, published in: Future Data and Security Engineering D. Zhou et al., “IoU Loss for 2D/3D Object Detection,” 2019 International Conference on 3D Vi...
A Model for Real-Time Traffic Signs Recognition Based on the YOLO Algorithm — A Case Study Using Vietnamese Traffic Signs Tran et al, 2019, published in: Future Data and Security Engineering D. Zhou et al., “IoU Loss for 2D/3D Object Detection,” 2019 International Conference on 3D Vi...
然后,分别将 VGG16 的全连接层 fc6 和 fc7 转换成3 \times 3卷积层 conv6 和1 \times 1卷积层 conv7,同时将池化层 pool5 由原来的stride=2的2\times 2变成stride=1的3\times 3,为了配合这种变化,采用了一种 Atrous Algorithm,就是 conv6 采用扩张卷积(空洞卷积),在不增加参数与模型复杂度的条件下指...
然后,分别将 VGG16 的全连接层 fc6 和 fc7 转换成 3×33×3 卷积层 conv6 和 1×11×1 卷积层 conv7,同时将池化层 pool5 由原来的 stride=2stride=2 的2×22×2 变成stride=1stride=1 的3×33×3,为了配合这种变化,采用了一种 Atrous Algorithm,就是 conv6 采用扩张卷积(空洞卷积),在不增加参数...
Application of local fully Convolutional Neural Network combined with YOLO v5 algorithm in small target detection of remote sensing image[J]. PloS one, 2021, 16(10): e0259283. 编辑于 2024-03-24 20:46・IP 属地上海 赞同添加评论 分享收藏喜欢收起 更多回答 宇航 Look...
Genetic algorithm used YOLOv3-SPP to train with GIoU loss and search 300 epochs for min-val 5k sets. We adopt searched learning rate 0.00261, momentum 0.949, IoU threshold for assigning ground truth 0.213, and loss normalizer 0.07 for genetic algorithm experiments. ...
Algorithm of Computer Mainboard Quality Detection for Real-Time Based on QD-YOLO. Electronics 2022, 11, 2424. https://doi.org/10.3390/electronics11152424 AMA Style Tu G, Qin J, Xiong NN. Algorithm of Computer Mainboard Quality Detection for Real-Time Based on QD-YOLO. Electronics. 2022; ...