Zobrazeno 1 - 10
of 103 118
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:
Gong-kuang zidonghua, Vol 50, Iss 8, Pp 91-98 (2024)
The existing foreign object detection methods for belt conveyors have problems such as weak capability to extract object semantic information, poor detection precision, and only recognizing and detecting foreign objects. The methods cannot accurately
Externí odkaz:
https://doaj.org/article/f8eea3b7206f40d08785910e6f4e7bcc
Publikováno v:
EURASIP Journal on Advances in Signal Processing, Vol 2024, Iss 1, Pp 1-18 (2024)
Abstract As unmanned vehicle technology advances rapidly, obstacle recognition and target detection are crucial links, which directly affect the driving safety and efficiency of unmanned vehicles. In response to the inaccurate localization of small t
Externí odkaz:
https://doaj.org/article/c6d466c1f16246049fee3911cfc2e6fc
Publikováno v:
Alexandria Engineering Journal, Vol 104, Iss , Pp 423-433 (2024)
In the realm of underwater object detection, conventional methodologies often encounter challenges in accurately identifying and detecting small targets. These difficulties stem primarily from the intricate nature of underwater environments, suboptim
Externí odkaz:
https://doaj.org/article/9dc5a1076cbd4184a3df90d840f00246
Publikováno v:
Alexandria Engineering Journal, Vol 104, Iss , Pp 46-55 (2024)
Fueled by substantial advancements in deep learning, the domain of autonomous driving is swiftly advancing towards more robust and effective intelligent systems. One of the critical challenges in this field is achieving accurate 3D object detection,
Externí odkaz:
https://doaj.org/article/070e95decc2246819aeee0b2f75a4d6c
Publikováno v:
Geo-spatial Information Science, Pp 1-15 (2024)
Accurate and efficient ship detection is crucial for ocean monitoring and management, especially in reefs and deep-sea, where fishing and illegal activities threaten sustainability of ecosystems. Obtaining the size of ships in reefs and deep-sea help
Externí odkaz:
https://doaj.org/article/8479101b8bfd40df922f80785ea7c699
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 17, Iss 1, Pp 1-18 (2024)
Abstract Insulator defect detection is a critical aspect of grid inspection in reality, yet it faces intricate environmental challenges, such as slow detection speed and low accuracy. To address this issue, we propose a YOLOv8-based insulator defect
Externí odkaz:
https://doaj.org/article/669b213b11fb405299c8b580207072d7
Publikováno v:
Demonstratio Mathematica, Vol 57, Iss 1, Pp 15-25 (2024)
Water is a vital resource essential to the survival and development of all creatures. With the rapid growth of industry and agriculture, people face a severe threat of ecological destruction and environmental pollution while living earthly lives. Wat
Externí odkaz:
https://doaj.org/article/d9a8059ec86746ee888dd0c28fd874d3
Autor:
Razak Rashad N., Abdullah Hadeel N.
Publikováno v:
Open Engineering, Vol 14, Iss 1, Pp 533-45 (2024)
Multi-object detection and tracking is a crucial and extensively researched field in image processing and computer vision. It involves predicting complete tracklets for many objects in a video clip concurrently. This article uses the frame cancellati
Externí odkaz:
https://doaj.org/article/0ea3b22557824f56911edcd216e19470
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-18 (2024)
Abstract Underwater object detection is a crucial aspect of monitoring the aquaculture resources to preserve the marine ecosystem. In most cases, Low-light and scattered lighting conditions create challenges for computer vision-based underwater objec
Externí odkaz:
https://doaj.org/article/647358280332479e91a9bd0f93ccfab9