Multi-Scale Ship Detection Algorithm Based on YOLOv7 for Complex Scene SAR ImagesDEEP learningSYNTHETIC aperture radarNAVAL architectureRADARSAT satellitesALGORITHMSSHIP modelsSHIPSRecently, deep learning techniques have been extensively used to detect ships in synthetic aperture radar (SAR) images. The ...
作者报告了YOLOv10在COCO数据集上的详细性能,包括在不同IoU阈值下的AP和AP,以及在不同尺度下的AP、AP和AP,具体数据见表15。 8 More Analyses for Holistic Efficiency-Accuracy Driven Model Design 作者注意到,由于模型规模较小,降低YOLOv10-S(表2中第2个)的延迟尤为具有挑战性。然而,如表2所示,作者以效率为...
SPP来源于ResNets作者何恺明的论文:Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition SPP就是将特征层分别通过一个池化核大小为5x5、9x9、13x13的最大池化层,然后在通道方向进行concat拼接在做进一步融合,这样能够在一定程度上解决目标多尺度问题,如下图所示。 (3)PAN PAN(Path Aggregat...
[12]YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications: https://arxiv.org/pdf/2209.02976.pdf [13]YOLOv6-PyTorch: https://github.com/meituan/YOLOv6 [14] YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors: https://arx...
论文:YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors 开源代码:mirrors / WongKinYiu / yolov7 · GitCode YOLO论文系列前期回顾: 【YOLO系列】YOLOv6论文超详细解读(翻译 +学习笔记) 【YOLO系列】YOLOv5超详细解读(网络详解) 【YOLO系列】YOLOv4论文超详细...
(videofilename.c_str(), &end, 10)); cap.open(i); } else { cap.open(videofilename); } } obj_det_filename = "testing " + obj_det_filename; //namedWindow(obj_det_filename, WINDOW_NORMAL); for (size_t i = 0;; i++) { Mat img; if (cap.isOpened()) { cap >> img; ...
2022.8.13 rename reop、 public new version、C++ for end2end 2022.8.11 nms plugin support ==> Now you can set --end2end flag while useexport.pyget a engine file 2022.7.8 support YOLOv7 2022.7.3 support TRT int8 post-training quantization ...
Consistent Dual Assignments for NMS-free Training 在训练期间,YOLOs通常利用TAL为每个实例分配多个阳性样本。一对多分配的采用产生了丰富的监控信号,有助于优化并实现卓越的性能。然而,YOLO必须依赖NMS后处理,这导致部署的推理效率不理想。虽然以前的工作探索一对一匹配来抑制冗余预测,但它们通常会引入额外的推理开销或...
欢迎关注我,获取我的更多笔记分享 大家好,我是极智视界,本文解读一下 更高、更快、更强的 YOLOv7:Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors。 在 5FPS 到 160 FPS…
(c1, c_, 1, 1)self.cv3 = Conv(c_, c_, 3, 1)self.cv4 = Conv(c_, c_, 1, 1)self.m = nn.ModuleList([nn.MaxPool2d(kernel_size=x, stride=1, padding=x // 2) for x in k])self.cv5 = Conv(4 * c_, c_, 1, 1)self.cv6 = Conv(c_, c_, 3, 1)self.cv7 = ...