Experiment results show that the proposed method can significantly enhance the accuracy of lightweight neural networks for object detection. We directly apply ...
Oct 2, 2021 · Experiment results show that the proposed method can significantly enhance the accu- racy of lightweight neural networks for object detection.
Experiment results show that the proposed method can significantly enhance the accuracy of lightweight neural networks for object detection. We directly apply ...
We propose an automated machine learning pipeline to study the power of lightweight neural networks. 2. We propose a learnable knowledge space translation.
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A lightweight YOLOv4 detection algorithm (KM-YOLOv4) improved by multi-scale feature fusion is proposed for the target detection of dense silkworms. The Kmeans ...
Jul 8, 2023 · This paper proposes a lightweight aluminum surface defect detection model, M2-BL-YOLOv4, based on the YOLOv4 algorithm.
Apr 16, 2024 · This study aims to introduce a more lightweight and quicker model—but with improved accuracy—for diagnosing malaria using a YOLOv4 (You Only ...
A lightweight YOLOv4 detection algorithm (KM-YOLOv4) improved by multi-scale feature fusion is proposed for the target detection of dense silkworms. The Kmeans ...
Numerous object detection algorithms exist, but many researchers agree that among the most efficient lightweight models are the YOLO algorithms (Redmon et al., ...
A lightweight YOLOv4 detection algorithm (KM-YOLOv4) improved by multi-scale feature fusion is proposed for the target detection of dense silkworms.