Jul 25, 2023 · The YOLO-SG approach employs SPD-Conv as a down-sampling structure to mitigate the loss of feature information during the down-sampling process.
Jun 3, 2024 · This study introduces the Space-to-Depth (SPD) module to address missed detections caused by multi-scale variations of traffic signs in traffic scenes.
Oct 29, 2024 · Detecting small traffic signs poses significant challenges due to the complex nature and dynamic conditions of real-world traffic scenarios.
Sep 27, 2024 · In the realm of traffic sign detection, challenges arise due to the small size of objects, complex scenes, varying scales of signs, ...
Oct 18, 2024 · The experimental results indicate that the EDN-YOLO method significantly enhances the capability of detecting multi-scale traffic signs in ...
This study proposes YOLOv8s-DDA, a tiny object detection method based on YOLOv8s, to address three elements of traffic sign identification issues: feature ...
Abstract. Traffic sign detection in real scenarios is challenging due to their complexity and small size, often preventing existing deep learning models.
By selectively focusing on relevant features, the attention mechanism helps the model better capture and understand the distinctive characteristics of traffic.
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The comparative experimental results indicates that the detection performance has been significantly enhanced in small objects and complex scenes. Table 1 ...
Nov 15, 2023 · It reduces the size of the feature map by slicing, and then assigns the channels of the sliced feature map through the channel attention ...