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    Why is yolov4 a good choice?YOLOv4 is designed to provide the optimal balance between speed and accuracy, making it an excellent choice for many applications. YOLOv4 architecture diagram. Showcasing the intricate network design of YOLOv4, including the backbone, neck, and head components, and their interconnected layers for optimal real-time object detection.
    What is a yolov4 object detector?A typical object detector is composed of several parts including the input, the backbone, the neck, and the head. The backbone of YOLOv4 is pre-trained on ImageNet and is used to predict classes and bounding boxes of objects. The backbone could be from several models including VGG, ResNet, ResNeXt, or DenseNet.
    How do I associate a repository with a yolobit topic?To associate your repository with the yolobit topic, visit your repo's landing page and select "manage topics." GitHub is where people build software. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects.
    What are the evaluation results for yolov3 & mixed Yolo Lite for shipdata?Evaluation results for YOLOv3 and Mixed YOLOv3-LITE for ShipData. 4.2.4. Performance Tests Based on Embedded Platform Mixed YOLOv3-LITE was tested with a Jetson AGX Xavier device; the results are shown in Table 10. When inputting an image with a size of 224 × 224, it reached 43 FPS.
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