Zobrazeno 1 - 10
of 197
pro vyhledávání: '"Object detection and recognition"'
Publikováno v:
Machines, Vol 12, Iss 8, p 557 (2024)
Autonomous vehicles face challenges in small-target detection and, in particular, in accurately identifying traffic lights under low visibility conditions, e.g., fog, rain, and blurred night-time lighting. To address these issues, this paper proposes
Externí odkaz:
https://doaj.org/article/c1a398002f4c40a2ad8d4cd48156c00a
Publikováno v:
Научный вестник МГТУ ГА, Vol 25, Iss 4, Pp 20-43 (2022)
The paper proposes a technology for automated video-based observation (VBO) of a drogue-sensor in the problem of aerial refueling. The technology is based on the use of a passive optoelectronic system and incorporates the logic of automated refueling
Externí odkaz:
https://doaj.org/article/3f476f45028549cd8e0f1413afcf206a
Autor:
Edeh Michael Onyema, Sundaravadivazhagn Balasubaramanian, Kanimozhi Suguna S, Celestine Iwendi, B.V.V. Siva Prasad, Chinecherem Deborah Edeh
Publikováno v:
Measurement: Sensors, Vol 27, Iss , Pp 100718- (2023)
Remote monitoring is the process that monitors and observes information from a distance utilizing sensors or electronic types of equipment. Remote monitoring is used in real-time applications like traffic, forest, military, shops, and hospitals to de
Externí odkaz:
https://doaj.org/article/49df9307f28d49f29815b3d5362bbfa1
Publikováno v:
IEEE Access, Vol 10, Pp 28471-28486 (2022)
While smart meters are still not widely installed in many countries, automatic reading of traditional-type meters is useful from the perspective of both cost and safety. Although convolutional neural network (CNN) showed a high potential for automati
Externí odkaz:
https://doaj.org/article/235f8d9a974f420ab46eff572232907c
Autor:
Muhammad Shoaib, Tariq Hussain, Babar Shah, Ihsan Ullah, Sayyed Mudassar Shah, Farman Ali, Sang Hyun Park
Publikováno v:
Frontiers in Plant Science, Vol 13 (2022)
Plants contribute significantly to the global food supply. Various Plant diseases can result in production losses, which can be avoided by maintaining vigilance. However, manually monitoring plant diseases by agriculture experts and botanists is time
Externí odkaz:
https://doaj.org/article/0e0c2d374e0e49ca9614d5a5cbb13792
Akademický článek
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Publikováno v:
IEEE Access, Vol 9, Pp 81564-81574 (2021)
The object detection and recognition algorithm based on the fusion of millimeter-wave radar and high-definition video data can improve the safety of intelligent-driving vehicles effectively. However, due to the different data modalities of millimeter
Externí odkaz:
https://doaj.org/article/1142a39c86d94730985e7406755fcecc
Autor:
Xian Sun, Peijin Wang, Zhiyuan Yan, Wenhui Diao, Xiaonan Lu, Zhujun Yang, Yidan Zhang, Deliang Xiang, Chen Yan, Jie Guo, Bo Dang, Wei Wei, Feng Xu, Cheng Wang, Ronny Hansch, Martin Weinmann, Naoto Yokoya, Kun Fu
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 8922-8940 (2021)
In this article, we introduce the 2020 Gaofen Challenge and relevant scientific outcomes. The 2020 Gaofen Challenge is an international competition, which is organized by the China High-Resolution Earth Observation Conference Committee and the Aerosp
Externí odkaz:
https://doaj.org/article/6221624fc71d4fc19ab93a8ddbde2b1a
Publikováno v:
Advanced Engineering Research, Vol 20, Iss 1, Pp 93-99 (2020)
Introduction. The problem of automatic license plate recognition is considered. Its solution has many potential applications from safety to traffic control. The work objective was to develop an intelligent recognition system based on the application
Externí odkaz:
https://doaj.org/article/31e447888b784aaba5f48fd31f53773d
Publikováno v:
IEEE Access, Vol 8, Pp 71739-71751 (2020)
Fisheye Images have attracted increasing attention from the research community due to their large field of view (LFOV). However, the geometric transformations inherent in fisheye cameras result in unknown spatial distortion and large variations in th
Externí odkaz:
https://doaj.org/article/fe36dafd2d8a4c8aac47c809e0188d6c