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    دورية أكاديمية
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    دورية أكاديمية

    المساهمون: Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education

    المصدر: IEEE Access ; volume 11, page 64185-64200 ; ISSN 2169-3536

  3. 3
    دورية أكاديمية

    المساهمون: Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education

    المصدر: IEEE Access ; volume 11, page 142734-142747 ; ISSN 2169-3536

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    دورية أكاديمية
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    دورية أكاديمية

    الوصف: IPIN 2019 Competition, sixth in a series of IPIN competitions, was held at the CNR Research Area of Pisa (IT), integrated into the program of the IPIN 2019 Conference. It included two on-site real-time Tracks and three off-site Tracks. The four Tracks presented in this paper were set in the same environment, made of two buildings close together for a total usable area of 1000 m 2 outdoors and and 6000 m 2 indoors over three floors, with a total path length exceeding 500 m. IPIN competitions, based on the EvAAL framework, have aimed at comparing the accuracy performance of personal positioning systems in fair and realistic conditions: past editions of the competition were carried in big conference settings, university campuses and a shopping mall. Positioning accuracy is computed while the person carrying the system under test walks at normal walking speed, uses lifts and goes up and down stairs or briefly stops at given points. Results presented here are a showcase of state-of-the-art systems tested side by side in real-world settings as part of the on-site real-time competition Tracks. Results for off-site Tracks allow a detailed and reproducible comparison of the most recent positioning and tracking algorithms in the same environment as the on-site Tracks.

    وصف الملف: application/pdf

    العلاقة: Development of human enhancement fire helmet and fire suppression support system; Basic Science Research Program; ICT Research and Development Program of MSIP/IITP (Development of Precise Positioning Technology for the Enhancement of Pedestrian Position/Spatial Cognition and Sports Competition Analysis); MICROCEBUS; REPNIN PLUS; TECHNOFUSION(III)CM; Development of wireless communication tracking-based location information system in disaster scene for fire-fighters and person who requested rescue; Strategic Priority Research Program; IEEE Access, Vol. 8 (2020); F. Potortì et al., "The IPIN 2019 Indoor Localisation Competition—Description and Results," in IEEE Access, vol. 8, pp. 206674-206718, 2020, doi:10.1109/ACCESS.2020.3037221.; http://hdl.handle.net/10234/200929Test

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    دورية أكاديمية

    المصدر: Sensors (14248220); Jan2024, Vol. 24 Issue 2, p522, 19p

    مصطلحات موضوعية: WEATHER, SANDSTORMS, COMPUTER vision, DEEP learning, RAINFALL

    مستخلص: Recent advancements in computer vision technology, developments in sensors and sensor-collecting approaches, and the use of deep and transfer learning approaches have excelled in the development of autonomous vehicles. On-road vehicle detection has become a task of significant importance, especially due to exponentially increasing research on autonomous vehicles during the past few years. With high-end computing resources, a large number of deep learning models have been trained and tested for on-road vehicle detection recently. Vehicle detection may become a challenging process especially due to varying light and weather conditions like night, snow, sand, rain, foggy conditions, etc. In addition, vehicle detection should be fast enough to work in real time. This study investigates the use of the recent YOLO version, YOLOx, to detect vehicles in bad weather conditions including rain, fog, snow, and sandstorms. The model is tested on the publicly available benchmark dataset DAWN containing images containing four bad weather conditions, different illuminations, background, and number of vehicles in a frame. The efficacy of the model is evaluated in terms of precision, recall, and mAP. The results exhibit the better performance of YOLOx-s over YOLOx-m and YOLOx-l variants. YOLOx-s has 0.8983 and 0.8656 mAP for snow and sandstorms, respectively, while its mAP for rain and fog is 0.9509 and 0.9524, respectively. The performance of models is better for snow and foggy weather than rainy weather sandstorms. Further experiments indicate that enhancing image quality using multiscale retinex improves YOLOx performance. [ABSTRACT FROM AUTHOR]

    : Copyright of Sensors (14248220) is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

  7. 7
    دورية أكاديمية

    المصدر: IEEE access, 8, 206674–206718 ; ISSN: 2169-3536

    الوصف: PIN 2019 Competition, sixth in a series of IPIN competitions, was held at the CNR Research Area of Pisa (IT), integrated into the program of the IPIN 2019 Conference. It included two on-site real-time Tracks and three off-site Tracks. The four Tracks presented in this paper were set in the same environment, made of two buildings close together for a total usable area of 1000 m 2 outdoors and and 6000 m 2 indoors over three floors, with a total path length exceeding 500 m. IPIN competitions, based on the EvAAL framework, have aimed at comparing the accuracy performance of personal positioning systems in fair and realistic conditions: past editions of the competition were carried in big conference settings, university campuses and a shopping mall. Positioning accuracy is computed while the person carrying the system under test walks at normal walking speed, uses lifts and goes up and down stairs or briefly stops at given points. Results presented here are a showcase of state-of-the-art systems tested side by side in real-world settings as part of the on-site real-time competition Tracks. Results for off-site Tracks allow a detailed and reproducible comparison of the most recent positioning and tracking algorithms in the same environment as the on-site Tracks.

    وصف الملف: application/pdf

    العلاقة: info:eu-repo/semantics/altIdentifier/wos/000594446900001; info:eu-repo/semantics/altIdentifier/issn/2169-3536; https://publikationen.bibliothek.kit.edu/1000130123Test; https://publikationen.bibliothek.kit.edu/1000130123/104023450Test; https://doi.org/10.5445/IR/1000130123Test

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    مؤتمر
  9. 9
    دورية أكاديمية

    الوصف: IPIN 2019 Competition, sixth in a series of IPIN competitions, was held at the CNR Research Area of Pisa (IT), integrated into the program of the IPIN 2019 Conference. It included two on-site real-time Tracks and three off-site Tracks. The four Tracks presented in this paper were set in the same environment, made of two buildings close together for a total usable area of 1000 m2 outdoors and and 6000 m2 indoors over three floors, with a total path length exceeding 500 m. IPIN competitions, based on the EvAAL framework, have aimed at comparing the accuracy performance of personal positioning systems in fair and realistic conditions: past editions of the competition were carried in big conference settings, university campuses and a shopping mall. Positioning accuracy is computed while the person carrying the system under test walks at normal walking speed, uses lifts and goes up and down stairs or briefly stops at given points. Results presented here are a showcase of state-of-the-art systems tested side by side in real-world settings as part of the on-site real-time competition Tracks. Results for off-site Tracks allow a detailed and reproducible comparison of the most recent positioning and tracking algorithms in the same environment as the on-site Tracks. ; The authors would like to thank Siemens, the Electronic and Telecommunications Research Institute (ETRI), the Korean Institute of Communications and Information Sciences (KICS), Ganko Food, J-Power Systems, and the other sponsors who provided prizes for the winners of the competition (see http://ipin-conference.org/2019/awards.htmlTest for a complete list).

    وصف الملف: application/pdf

    العلاقة: https://ieeexplore.ieee.org/document/9253514Test; F. Potortì et al., "The IPIN 2019 Indoor Localisation Competition—Description and Results," in IEEE Access, vol. 8, pp. 206674-206718, 2020, doi:10.1109/ACCESS.2020.3037221; http://hdl.handle.net/1822/70552Test

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    دورية أكاديمية