Zobrazeno 1 - 10
of 104 353
pro vyhledávání: '"Object Detection"'
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 10, Pp 2727-2737 (2024)
The advantage of deep detection models primarily benefits from the feature representation ability of the backbone network, where down-sampling plays a key role in semantic integration. However, existing down-sampling approaches often ignore the globa
Externí odkaz:
https://doaj.org/article/47bc19d11c5f453baaf3cdaec22604fd
Publikováno v:
International Journal of Intelligent Computing and Cybernetics, 2024, Vol. 17, Issue 4, pp. 805-823.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IJICC-01-2024-0020
Publikováno v:
Alexandria Engineering Journal, Vol 107, Iss , Pp 786-798 (2024)
Wheat yellow rust disease poses a significant threat to global wheat yield and grain quality. Early detection of this disease will help to minimize the loss caused by its effects. Existing models work well on images taken in a controlled environment,
Externí odkaz:
https://doaj.org/article/39d541cb7ca04c53b9e22e7f3f4a257c
Autor:
Muhammad Zakir Shaikh, Zeeshan Ahmed, Enrique Nava Baro, Samreen Hussain, Mariofanna Milanova
Publikováno v:
Alexandria Engineering Journal, Vol 107, Iss , Pp 533-546 (2024)
The Train Rolling-Stock Examination (TRSE) is a safety examination process that physically examines the bogie parts of a moving train, typically at speeds over 30 km/h. Currently, this inspection process is done manually by railway personnel in many
Externí odkaz:
https://doaj.org/article/0129aa0264a5422a99160894b6098506
Publikováno v:
Alexandria Engineering Journal, Vol 106, Iss , Pp 298-311 (2024)
Object detection in road scenarios is crucial for intelligent transport systems and autonomous driving, but complex traffic conditions pose significant challenges. This paper introduces Z-You Only Look Once version 8 small (Z-YOLOv8s), designed to im
Externí odkaz:
https://doaj.org/article/a484d38475514a11b7a2475814ea83d5
Autor:
Zhenfeng Shao, Yu Wang, Jiaming Wang, Lianbing Deng, Xiao Huang, Tao Lu, Fang Luo, Ruiqian Zhang
Publikováno v:
Geo-spatial Information Science, Pp 1-15 (2024)
In this paper, we introduce a challenging Global Large-scale Ship Database (GLSD), designed specifically for ship detection tasks. The designed GLSD database includes a total of 212,357 annotated instances from 152,576 images. Based on the collected
Externí odkaz:
https://doaj.org/article/b4c0aea141034ffc99cbfb1a0444b71a
Publikováno v:
Virtual Reality & Intelligent Hardware, Vol 6, Iss 5, Pp 396-407 (2024)
Background: Co-salient object detection (Co-SOD) aims to identify and segment commonly salient objects in a set of related images. However, most current Co-SOD methods encounter issues with the inclusion of irrelevant information in the co-representa
Externí odkaz:
https://doaj.org/article/f7288b9828e84e50b761d2e35b05ca14
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-20 (2024)
Abstract The accurate recognition of apples in complex orchard environments is a fundamental aspect of the operation of automated picking equipment. This paper aims to investigate the influence of dense targets, occlusion, and the natural environment
Externí odkaz:
https://doaj.org/article/851ecc9cbab547f985de1e43d3146fb9
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract Rapid and reliable detection of human survivors trapped under debris is crucial for effective post-earthquake search and rescue (SAR) operations. This paper presents a novel approach to survivor detection using a snake robot equipped with de
Externí odkaz:
https://doaj.org/article/f28587f684d247a594af909cba92ceac
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-17 (2024)
Abstract Accurate detection of asphalt pavement distress is crucial for road maintenance and traffic safety. However, traditional convolutional neural networks usually struggle with this task due to the varied distress patterns and complex background
Externí odkaz:
https://doaj.org/article/0038bf45301e473b87464688165ee097