Zobrazeno 1 - 10
of 89
pro vyhledávání: '"Jianqin, Yin"'
Autor:
Zhicheng Zhang, Jianqin Yin
Publikováno v:
IEEE Access, Vol 8, Pp 16269-16280 (2020)
Multi-level thresholding is one of the essential approaches for image segmentation. Determining the optimal thresholds for multi-level thresholding needs exhaustive searching which is time-consuming. To improve the searching efficiency, a novel popul
Externí odkaz:
https://doaj.org/article/f5729906a631473ca8f0b1b00e87f6f4
Publikováno v:
IEEE Access, Vol 8, Pp 157037-157049 (2020)
Individual commute time recognition is essential for traffic demand management. However, this problem has yet to be studied. In this study, we propose a hierarchical semantic model (HSM) to recognize individual commute time. To the best of our knowle
Externí odkaz:
https://doaj.org/article/cce22c4edfa74d5eb523212e550a7845
Publikováno v:
IEEE Access, Vol 7, Pp 119813-119822 (2019)
Short text is an important form of information dissemination and opinion expression in various social media platforms. Sentiment analysis of short texts is beneficial for the understanding of customers' emotional state, obtaining customers' opinions
Externí odkaz:
https://doaj.org/article/e8ca31b7c8674e648b5dfcc803c2b297
Autor:
Xiaoli Liu, Jianqin Yin
Publikováno v:
Applied Sciences, Vol 12, Iss 11, p 5381 (2022)
Action prediction is an important task in human activity analysis, which has many practical applications, such as human–robot interactions and autonomous driving. Action prediction often comprises two subtasks: action semantic prediction and future
Externí odkaz:
https://doaj.org/article/b7f163981634482ba9803eb76527efdd
Publikováno v:
Applied Sciences, Vol 12, Iss 8, p 3764 (2022)
We propose a fully convolutional neural network based on the attention mechanism for 3D medical image segmentation tasks. It can adaptively learn to highlight the salient features of images that are useful for image segmentation tasks. Some prior met
Externí odkaz:
https://doaj.org/article/ddf24fbc4f1646ec859c42b232c14a14
Publikováno v:
Applied Sciences, Vol 12, Iss 8, p 4061 (2022)
Amodal segmentation is a new direction of instance segmentation while considering the segmentation of the visible and occluded parts of the instance. The existing state-of-the-art method uses multi-task branches to predict the amodal part and the vis
Externí odkaz:
https://doaj.org/article/97e58920a99247308ca3f1be6e6296e6
Publikováno v:
IEEE Access, Vol 6, Pp 31677-31684 (2018)
This research proposes a method for optimizing extracted candidate proposals based on the action temporal semantic continuity rule to accurately detect the category and start and end time in the temporal action detection of long untrimmed videos. Fir
Externí odkaz:
https://doaj.org/article/ded6546dd60d44638f1727d6803470f1
Publikováno v:
IEEE Access, Vol 6, Pp 17913-17922 (2018)
Human action recognition is one of the fundamental challenges in robotics systems. In this paper, we propose one lightweight action recognition architecture based on deep neural networks just using RGB data. The proposed architecture consists of conv
Externí odkaz:
https://doaj.org/article/dfc201b37e5246aa93d59f56c0e38c59
Publikováno v:
IEEE Robotics and Automation Letters. 7:10097-10104
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0bfa01eba3f289d6d35cb022076afaea
https://doi.org/10.1109/lra.2022.3185768
https://doi.org/10.1109/lra.2022.3185768
Autor:
Pengxiang Ding, Jianqin Yin
Publikováno v:
IEEE Transactions on Circuits and Systems for Video Technology. 32:5846-5858
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7ccf032fcf40a4f0b291da0b6eb19575
https://doi.org/10.1109/tcsvt.2022.3163782
https://doi.org/10.1109/tcsvt.2022.3163782