Zobrazeno 1 - 10
of 131
pro vyhledávání: '"John See"'
Publikováno v:
Machines, Vol 11, Iss 10, p 953 (2023)
The processing of aerial images taken by drones is a challenging task due to their high resolution and the presence of small objects. The scale of the objects varies diversely depending on the position of the drone, which can result in loss of inform
Externí odkaz:
https://doaj.org/article/54952526b7d34e29bbd9360156471dff
Autor:
Rasoul Banaeeyan, Hezerul Abdul Karim, Haris Lye, Mohammad Faizal Ahmad Fauzi, Sarina Mansor, John See
Publikováno v:
International Journal of Technology, Vol 10, Iss 7, Pp 1335-1343 (2019)
The main objective of this paper is pornography recognition using audio features. Unlike most of the previous attempts, which have concentrated on the visual content of pornography images or videos, we propose to take advantage of sounds. Using s
Externí odkaz:
https://doaj.org/article/f01074af094349ab9b452e74b9e94f16
Publikováno v:
EURASIP Journal on Image and Video Processing, Vol 2017, Iss 1, Pp 1-18 (2017)
Abstract Human action recognition is an increasingly matured field of study in the recent years, owing to its widespread use in various applications. A number of related research problems, such as feature representations, human pose and body parts de
Externí odkaz:
https://doaj.org/article/70e6d60e78c742c19776f89dcdb78c3a
Autor:
Abdulaziz Saleh Ba Wazir, Hezerul Abdul Karim, Mohd Haris Lye Abdullah, Nouar AlDahoul, Sarina Mansor, Mohammad Faizal Ahmad Fauzi, John See, Ahmad Syazwan Naim
Publikováno v:
Sensors, Vol 21, Iss 3, p 710 (2021)
Given the excessive foul language identified in audio and video files and the detrimental consequences to an individual’s character and behaviour, content censorship is crucial to filter profanities from young viewers with higher exposure to uncens
Externí odkaz:
https://doaj.org/article/fb15ef057e8643f0b500540b467ece34
Autor:
Nouar AlDahoul, Hezerul Abdul Karim, Mohd Haris Lye Abdullah, Mohammad Faizal Ahmad Fauzi, Abdulaziz Saleh Ba Wazir, Sarina Mansor, John See
Publikováno v:
Symmetry, Vol 13, Iss 1, p 26 (2020)
Video pornography and nudity detection aim to detect and classify people in videos into nude or normal for censorship purposes. Recent literature has demonstrated pornography detection utilising the convolutional neural network (CNN) to extract featu
Externí odkaz:
https://doaj.org/article/23c335d6927746fc92b4b579e5c35672
Publikováno v:
Sensors, Vol 20, Iss 11, p 3045 (2020)
Collecting correlated scene images and camera poses is an essential step towards learning absolute camera pose regression models. While the acquisition of such data in living environments is relatively easy by following regular roads and paths, it is
Externí odkaz:
https://doaj.org/article/41d47f4ca5d14de2b10387df5f3a95dc
Publikováno v:
Frontiers in Psychology, Vol 9 (2018)
Over the last few years, automatic facial micro-expression analysis has garnered increasing attention from experts across different disciplines because of its potential applications in various fields such as clinical diagnosis, forensic investigation
Externí odkaz:
https://doaj.org/article/2f9ed3c955d240ccb1d64a1947eac1e7
Efficient spatio-temporal local binary patterns for spontaneous facial micro-expression recognition.
Publikováno v:
PLoS ONE, Vol 10, Iss 5, p e0124674 (2015)
Micro-expression recognition is still in the preliminary stage, owing much to the numerous difficulties faced in the development of datasets. Since micro-expression is an important affective clue for clinical diagnosis and deceit analysis, much effor
Externí odkaz:
https://doaj.org/article/2bd1fa582b774bac81f0e18217021417
Publikováno v:
Renewable Energy. 203:267-279
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4449083441cca2b6fb334be2f925579b
https://doi.org/10.1016/j.renene.2022.12.063
https://doi.org/10.1016/j.renene.2022.12.063
Publikováno v:
IEEE Transactions on Image Processing. 32:694-708
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2fac96a919d605d1744089315561c0c8
https://doi.org/10.1109/tip.2022.3232232
https://doi.org/10.1109/tip.2022.3232232