Zobrazeno 1 - 10
of 1 468
pro vyhledávání: '"context information"'
Publikováno v:
Complex & Intelligent Systems, Vol 10, Iss 6, Pp 8095-8108 (2024)
Abstract Prohibited item detection is crucial for the safety of public places. Deep learning, one of the mainstream methods in prohibited item detection tasks, has shown superior performance far beyond traditional prohibited item detection methods. H
Externí odkaz:
https://doaj.org/article/d484803ea4e94f1398b877c6caf694a2
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-18 (2024)
Abstract Printed Circuit Boards (PCBs) are key devices for the modern-day electronic technologies. During the production of these boards, defects may occur. Several methods have been proposed to detect PCB defects. However, detecting significantly sm
Externí odkaz:
https://doaj.org/article/0dfb8798816f4d8aa908b337694fcc99
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 5, Pp 1197-1210 (2024)
Recommender systems provide important functions in areas such as dealing with data overload, providing personalized consulting services, and assisting clients in investment decisions. However, the cold start problem in recommender systems has always
Externí odkaz:
https://doaj.org/article/ba7e441673af4d86810c7904b4ba325d
Autor:
WANG Yan, NAN Peiqi
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 3, Pp 707-717 (2024)
In the task of image semantic segmentation, most methods do not make full use of features of different scales and levels, but directly upsampling, which will cause some effective information to be dismissed as redundant information, thus reducing the
Externí odkaz:
https://doaj.org/article/f6167a07c984425d843dae0797716d23
Autor:
Gayathri Dhara, Ravi Kant Kumar
Publikováno v:
Frontiers in Computer Science, Vol 6 (2024)
Recent research shows that Conditional Generative Adversarial Networks (cGANs) are effective for Salient Object Detection (SOD), a challenging computer vision task that mimics the way human vision focuses on important parts of an image. However, impl
Externí odkaz:
https://doaj.org/article/6e45de33ef1541d78ab66ba2b0e180a9
Publikováno v:
PeerJ Computer Science, Vol 10, p e2199 (2024)
Accurate localization of objects of interest in remote sensing images (RSIs) is of great significance for object identification, resource management, decision-making and disaster relief response. However, many difficulties, like complex backgrounds,
Externí odkaz:
https://doaj.org/article/9121eb141249433ebc2b89b7c1a89bb1
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 12138-12152 (2024)
Water body extraction is an essential mission in the field of semantic segmentation of remote sensing images. It plays a significant role in natural disaster prevention, water resources utilization, hydrological monitoring, and other territories. In
Externí odkaz:
https://doaj.org/article/685846f7eb174f3e817357dbdc24d737
Publikováno v:
IEEE Access, Vol 12, Pp 76392-76403 (2024)
In pedestrian detection, small-scale pedestrians often face challenges such as limited pixel values and insufficient features, often leading to wrong or missed detection. Therefore, this paper proposed a multi-scale structure perception and global co
Externí odkaz:
https://doaj.org/article/b006313ea342412f89ea9b189d5639fe
Publikováno v:
IEEE Access, Vol 12, Pp 45986-46001 (2024)
Rotated object detection in remote sensing images presents a highly challenging task due to the extensive fields of view and complex backgrounds. While Convolutional Neural Networks (CNNs) and Transformer networks have made progress in this area, the
Externí odkaz:
https://doaj.org/article/1964e4c41b044bfaadb25517d9290508
Publikováno v:
International Journal of Digital Earth, Vol 16, Iss 1, Pp 1-30 (2023)
Qinghai-Tibet Plateau lakes are important carriers of water resources in the ‘Asian’s Water Tower’, and it is of great significance to grasp the spatial distribution of plateau lakes for the climate, ecological environment, and regional water c
Externí odkaz:
https://doaj.org/article/d45f1446414b45d8bf57e3a2d1060f86