Zobrazeno 1 - 10
of 1 449
pro vyhledávání: '"Yolov5s"'
Publikováno v:
Shanghai Jiaotong Daxue xuebao, Vol 58, Iss 11, Pp 1816-1825 (2024)
The visual assistance driving system for civil aviation aircraft captures information about the surrounding threat scenario using airborne visual sensors, providing pilots with additional information to aid decision-making. However, the threat object
Externí odkaz:
https://doaj.org/article/8305970f5cf14ef685b5adc793978075
Publikováno v:
Zhongguo Jianchuan Yanjiu, Vol 19, Iss 5, Pp 200-207 (2024)
ObjectiveThis paper proposes a lightweight remote sensing ship target detection algorithm LR-YOLO based on improved YOLOv5s to meet the lightweight and fast inference requirements of ship target detection tasks involving remote sensing images. Method
Externí odkaz:
https://doaj.org/article/c17f0a496193402da48895a65dc798f0
Publikováno v:
Zhongguo Jianchuan Yanjiu, Vol 19, Iss 5, Pp 180-187 (2024)
ObjectiveA lightweight and efficient ship detection method based on the YOLO-FNC model is proposed for complex environments such as ports with dense traffic. MethodFirst, a FasterNeXt neural network module is designed on the basis of the FasterNet me
Externí odkaz:
https://doaj.org/article/ed02247a67f5437ea3d67c2f4cd43d83
Publikováno v:
工程科学学报, Vol 46, Iss 9, Pp 1647-1658 (2024)
Traffic sign detection and recognition facilitates real-time monitoring and interpretation of various traffic signs on the road, such as those indicating speed limits, prohibition of overtaking, and navigation cues. This has substantial applications
Externí odkaz:
https://doaj.org/article/f2d176f3748547e0a2cfd8d264c21796
Publikováno v:
Gong-kuang zidonghua, Vol 50, Iss 7, Pp 89-97 (2024)
At present, the combination of edge computing and machine vision has a good application prospect for coal mine safety monitoring. But the storage space and computing resources at the edge are limited, and high-precision complex visual models are diff
Externí odkaz:
https://doaj.org/article/73267469762249a39e7b9c107740a9d4
Publikováno v:
Energy Science & Engineering, Vol 12, Iss 7, Pp 2864-2878 (2024)
Abstract Real‐time monitoring of the coal caving process in fully mechanized mining is crucial for achieving intelligent and efficient top‐coal caving. While the coal gangue identification method, employing vision and deep learning, has advanced
Externí odkaz:
https://doaj.org/article/3c8ece58d5684752ba3b3862d910e172
Publikováno v:
Metalurgija, Vol 64, Iss 1-2, Pp 94-96 (2025)
In order to improve the accuracy of surface defect detection of high temperature casting slab, an improved YOLOv5s surface defect detection algorithm is proposed. Firstly, Swin Transformer network structure is added to enhance the ability of feature
Externí odkaz:
https://doaj.org/article/16e67b84de6b4e0ab41c9d7915676c91
Autor:
Mohan Arava, Divya Meena Sundaram
Publikováno v:
PeerJ Computer Science, Vol 10, p e2447 (2024)
Several factors cause vehicle accidents during driving, such as driver negligence, drowsiness, and fatigue. These accidents can be prevented if drivers receive timely warnings. Additionally, recent advancements in computer vision and artificial intel
Externí odkaz:
https://doaj.org/article/7e110b2a18cc4300aeb7b7ab76a2eec0
Publikováno v:
Ecological Informatics, Vol 83, Iss , Pp 102794- (2024)
Rapid and accurate detection of bamboo aphids can help prevent large-scale aphid infestations from occurring, which is of great significance for increasing bamboo shoot production and economic benefits. Herein, a lightweight and accurate model, SCA-Y
Externí odkaz:
https://doaj.org/article/cbf7ac9e3b244559aafc3536d490b850
Publikováno v:
Meitan kexue jishu, Vol 52, Iss 6, Pp 226-237 (2024)
Aiming at the complex working conditions environmental factors such as high noise, low illumination, motion blur and mass gangue mixing in coal mines, which lead to the problems of misdetection, omission and low detection accuracy in gangue recogniti
Externí odkaz:
https://doaj.org/article/ed8bc16f5ce145ba9ea616286fe44827