Zobrazeno 1 - 10
of 403
pro vyhledávání: '"Hairong Qi"'
Publikováno v:
Animals, Vol 13, Iss 17, p 2719 (2023)
Mobility is a vital welfare indicator that may influence broilers’ daily activities. Classical broiler mobility assessment methods are laborious and cannot provide timely insights into their conditions. Here, we proposed a semi-supervised Deep Lear
Externí odkaz:
https://doaj.org/article/e2ec72e45cfc4a0197da63247ee0b080
Publikováno v:
Animals, Vol 11, Iss 3, p 916 (2021)
Audio data collected in commercial broiler houses are mixed sounds of different sources that contain useful information regarding bird health condition, bird behavior, and equipment operation. However, characterizations of the sounds of different sou
Externí odkaz:
https://doaj.org/article/1a913ce210ea4985823ab3cea141d3d9
Publikováno v:
Sensors, Vol 2, Iss 7, Pp 286-293 (2002)
Advances in sensor technology and wireless communications have made networked microsensors possible, where each sensor individually senses the environment but collaboratively achieves complex information gathering and dissemination tasks. These netwo
Externí odkaz:
https://doaj.org/article/7cd10dd2a2f14e888b217c8678b5897f
Autor:
Yang Bai, Hairong Qi
Publikováno v:
EURASIP Journal on Image and Video Processing, Vol 2010 (2010)
Externí odkaz:
https://doaj.org/article/2234e2523ace4ee88f7c674ed411a7af
Autor:
Raul A. Almeida, Qing Cao, Jayne Wu, Shigetoshi Eda, Hairong Qi, Fanqi Wang, Yunhe Feng, S. J. Ivey, Haoran Niu
Publikováno v:
IEEE Internet of Things Journal. 9:10130-10138
Effective and efficient animal disease detection and control have drawn increasing attention in smart farming in recent years. It is crucial to explore how to harvest data and enable data-driven decision making for rapid diagnosis and early treatment
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7b5aba1410475cf1dc8d4829d731044f
https://doi.org/10.1109/jiot.2021.3122341
https://doi.org/10.1109/jiot.2021.3122341
Towards Personalized Privacy-Preserving Incentive for Truth Discovery in Mobile Crowdsensing Systems
Publikováno v:
IEEE Transactions on Mobile Computing. 21:352-365
Incentive mechanisms are essential for stimulating adequate worker participation to achieve good truth discovery performance in mobile crowdsensing (MCS) systems. However, most of existing incentive mechanisms only consider compensating workers' sens
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fd1e1b618cfdff8d3d2440a50df2cd13
https://doi.org/10.1109/tmc.2020.3003673
https://doi.org/10.1109/tmc.2020.3003673
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 60:1-23
Given the prior information of the target, hyperspectral target detection focuses on exploiting spectral differences to separate objects of interest from the background, which can be treated as information retrieval (IR) task in machine learning (ML)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::40099700a8b14e2f98d595fbb856fb22
https://doi.org/10.1109/tgrs.2021.3075583
https://doi.org/10.1109/tgrs.2021.3075583
Publikováno v:
2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::15dd376202da3b662d21fb340e0c70cb
https://doi.org/10.1109/wacv56688.2023.00379
https://doi.org/10.1109/wacv56688.2023.00379
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 59:8615-8629
Hyperspectral unmixing is an important problem for remotely sensed data interpretation. It amounts at estimating the spectral signatures of the pure spectral constituents in the scene (endmembers) and their corresponding subpixel fractional abundance
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c0b22aace752b42df5a11c440cafce0d
https://doi.org/10.1109/tgrs.2020.3041157
https://doi.org/10.1109/tgrs.2020.3041157
Publikováno v:
IEEE Transactions on Vehicular Technology. 70:6108-6121
Cell selection is a critical issue in sparse mobile crowdsensing (MCS) systems. However, the sensing cost heterogeneity among different cells (subareas) has long been ignored by existing works. Moreover, the data provided by participants are not alwa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::02f41981ebbc470182f15e525abc5c1d
https://doi.org/10.1109/tvt.2021.3077112
https://doi.org/10.1109/tvt.2021.3077112