In this paper, a lightweight and improved algorithm based on YOLOv4 is proposed and introduced into the electric bicycle detection task. Based on the of YOLOv4 ...
A diagnosis scheme is proposed to detect E-bikes' abnormal charging from the alternating current (AC) side of the charging pile.
This paper designs an electric vehicle monitoring system based on deep learning. The system uses the image real-time transmission system and deep learning ...
Sep 1, 2024 · The objective of this paper is to optimize the energy consumption and performance of fuel cell electric bicycles (FCEBs) under specific key input parameters.
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Sep 19, 2021 · In this study aimed to solve the object detection problem using deep learning. The bicycle object has been detected on the Coco data set and the MobileNet ...
The capability of deep neural networks to automatically learn complex and nonlinear patterns from observed data makes it applicable to a wide range of problems, ...
[PDF] Detection and Alarm of E-bike Intrusion in Elevator Scene
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With the deep learning, conventional object detection can obtain satisfactory results. However, some object detection problems with serious occlusions still ...
To meet the need for fast detection and identification of electric bicycles in elevators, we designed a modified YOLOv5-based identification approach in this ...
Jun 8, 2024 · This paper proposes an efficient electric bicycle tracking algorithm, EBTrack, utilizing the high-precision and lightweight YOLOv7 as the target detector.
Jun 29, 2022 · Compared with the traditional CNN deep learning model, the DeiT model has better performance in all four indicators. Only focusing on monitoring ...