Remote Vehicle Exhaust Detection Based on Integrated Deep Learning Models for Environmental Monitoring
The traditional equipment for tailpipe emission monitoring basically adopts the static fixed-point detection mode. Not only does this detection mode fail to ensure accurate analysis of vehicle exhaust emissions during dynamic operation, but its measurement results are also susceptible to interferenc...
出版年: | Journal of Network Intelligence |
---|---|
第一著者: | 2-s2.0-85219389947 |
フォーマット: | 論文 |
言語: | English |
出版事項: |
Taiwan Ubiquitous Information CO LTD
2025
|
オンライン・アクセス: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85219389947&partnerID=40&md5=921691be732cb284c461dcf19932b434 |
類似資料
-
Object detection for autonomous vehicle with Lidar using deep learning
著者:: 2-s2.0-85098280266
出版事項: (2020) -
Review of environmental monitoring in freshwater lakes using geospatial techniques (remote sensing and GIS)
著者:: Kamaruzzaman, 等
出版事項: (2025) -
Review of environmental monitoring in freshwater lakes using geospatial techniques (remote sensing and GIS)
著者:: Kamaruzzaman K.; Salleh S.A.; Pardi F.; Abdullah M.F.; Foronda V.; Bergonio E.L.; Rahmawaty R.
出版事項: (2025) -
Thermoelectric power generations from vehicle exhaust gas with TiO2 nanofluid cooling
著者:: 2-s2.0-85085129681
出版事項: (2020) -
Vehicle detection and tracking using YOLO and DeepSORT
著者:: 2-s2.0-85107642947
出版事項: (2021)