Zobrazeno 1 - 10
of 168
pro vyhledávání: '"DETECTION HEAD"'
Autor:
Yuliang Fu, Weiheng Li, Gang Li, Yuanzhi Dong, Songlin Wang, Qingyang Zhang, Yanbin Li, Zhiguang Dai
Publikováno v:
Frontiers in Plant Science, Vol 15 (2024)
IntroductionIn the field of facility agriculture, the accurate identification of tomatoes at multiple stages has become a significant area of research. However, accurately identifying and localizing tomatoes in complex environments is a formidable ch
Externí odkaz:
https://doaj.org/article/e545f4e3b8754cc08504658e1a5103f9
Publikováno v:
Gong-kuang zidonghua, Vol 50, Iss 8, Pp 99-104, 111 (2024)
The existing methods for detecting foreign objects in underground coal mine conveyor belts have poor adaptability to complex scenarios, cannot meet real-time and lightweight requirements, and perform poorly when dealing with foreign objects with larg
Externí odkaz:
https://doaj.org/article/f64a2dfb032344e58465c7942f2b6b0c
Publikováno v:
Frontiers in Physics, Vol 12 (2024)
In industrial aluminum sheet surface defect detection, false detection, missed detection, and low efficiency are prevalent challenges. Therefore, this paper introduces an improved YOLOv8 algorithm to address these issues. Specifically, the C2f-DSConv
Externí odkaz:
https://doaj.org/article/7722848b18da46409c9d9d15d982a5dd
Publikováno v:
IEEE Access, Vol 12, Pp 134008-134019 (2024)
Road defect detection is crucial for enhancing traffic safety, optimizing urban management efficiency, and promoting sustainable urban development. Traditional manual detection methods are inefficient and costly, and most deep learning-based road def
Externí odkaz:
https://doaj.org/article/5357b74307c74d0596071a1daac3da49
Publikováno v:
Metalurgija, Vol 63, Iss 3-4, Pp 399-402 (2024)
In response to the inevitable surface defects in the manufacturing process of hot-rolled steel, this paper proposes an improved steel surface defect detection model based on YOLOv7. In the Extended Efficient Large Aggregation Network (E-ELAN), the mo
Externí odkaz:
https://doaj.org/article/aa37821013e74d5ea2aae76834f9b836
Publikováno v:
IEEE Access, Vol 12, Pp 29690-29697 (2024)
Since the UAV is far away from the detected target when performing target detection at high altitudes, there is a significant difference in the size of the detected object, and there are problems such as the detected target being blocked by the objec
Externí odkaz:
https://doaj.org/article/75f24000b8674f6c9cc4ceb71e799b9b
Publikováno v:
Remote Sensing, Vol 16, Iss 21, p 4112 (2024)
Fire and smoke detection technologies face challenges in complex and dynamic environments. Traditional detectors are vulnerable to background noise, lighting changes, and similar objects (e.g., clouds, steam, dust), leading to high false alarm rates.
Externí odkaz:
https://doaj.org/article/59e4c937f71a4e258296b6c02fc61df0
Authenticity identification method for calligraphy regular script based on improved YOLOv7 algorithm
Autor:
Jinyuan Chen, Zucheng Huang, Xuyao Jiang, Hai Yuan, Weijun Wang, Jian Wang, Xintong Wang, Zheng Xu
Publikováno v:
Frontiers in Physics, Vol 12 (2024)
A regular calligraphy script of each calligrapher has unique strokes, and a script’s authenticity can be identified by comparing them. Hence, this study introduces a method for identifying the authenticity of regular script calligraphy works based
Externí odkaz:
https://doaj.org/article/66e1c4ac3eff4433a6ad6c1872b62db7
Publikováno v:
PeerJ Computer Science, Vol 10, p e2021 (2024)
To resolve the challenges of low detection accuracy and inadequate real-time performance in road scene detection, this article introduces the enhanced algorithm SDG-YOLOv5. The algorithm incorporates the SIoU Loss function to accurately predict the a
Externí odkaz:
https://doaj.org/article/4703e09678794edfb6398b7356735371
Publikováno v:
Fishes, Vol 9, Iss 9, p 338 (2024)
Target detection technology plays a crucial role in fishery ecological monitoring, fishery diversity research, and intelligent aquaculture. Deep learning, with its distinct advantages, provides significant convenience to the fishery industry. However
Externí odkaz:
https://doaj.org/article/ab585b28ea5f418c82e92f5285bb68fc