Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Henry Wing Fung Yeung"'
Publikováno v:
IEEE Transactions on Circuits and Systems for Video Technology. 30:1078-1091
Model drifting is one of the knotty problems that seriously restricts the accuracy of discriminative trackers in visual tracking. Most existing works usually focus on improving the robustness of the target appearance model. However, they are prone to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2068a36c5552c1d9bf1a92e6badef01c
https://doi.org/10.1109/tcsvt.2019.2902883
https://doi.org/10.1109/tcsvt.2019.2902883
Despite the recent progress in light field super-resolution (LFSR) achieved by convolutional neural networks, the correlation information of light field (LF) images has not been sufficiently studied and exploited due to the complexity of 4D LF data.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d74304f7241e2f6edaa257a48d1de6c6
Autor:
Grant Moule, Weidong Cai, Mohammed Bennamoun, Henry Wing Fung Yeung, Meng Zhou, Wanli Ouyang, Yuk Ying Chung, Wayne Thompson
Publikováno v:
Expert Systems with Applications. 191:116210
Satellite images have become more easily accessible due to government programs and the availability of commercial earth observation satellites. The increased volume of data and the recent advancement in deep learning-based techniques have made possib
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9587061d83008f931366d250c785fbb5
https://doi.org/10.1016/j.eswa.2021.116210
https://doi.org/10.1016/j.eswa.2021.116210
Publikováno v:
Multimedia Tools and Applications. 78:29211-29227
Image classification is a well-studied problem. However, there remains challenges for some special categories of images. This paper proposes a new deep convolutional neural network to improve image classification using extra light-field angular infor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::050a017e6aa921e05f09210fe3dd8de8
https://doi.org/10.1007/s11042-018-6597-x
https://doi.org/10.1007/s11042-018-6597-x
Publikováno v:
Applied Soft Computing. 66:319-329
Large number of object trackers based on particle swarm optimization (PSO) and its variants have been published in the recent decade. However, the majority of algorithms does not perform well when evaluated against the online object tracking benchmar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3ca92f59b964f4730563a23e2c548466
https://doi.org/10.1016/j.asoc.2018.02.037
https://doi.org/10.1016/j.asoc.2018.02.037
Publikováno v:
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society.
Light field (LF) photography is an emerging paradigm for capturing more immersive representations of the real-world. However, arising from the inherent trade-off between the angular and spatial dimensions, the spatial resolution of LF images captured
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::36eeb8a008db7a0f6d12e6528d791089
https://pubmed.ncbi.nlm.nih.gov/30530364
https://pubmed.ncbi.nlm.nih.gov/30530364
Publikováno v:
Computer Vision – ECCV 2018 ISBN: 9783030012304
ECCV (6)
ECCV (6)
Densely-sampled light fields (LFs) are beneficial to many applications such as depth inference and post-capture refocusing. However, it is costly and challenging to capture them. In this paper, we propose a learning based algorithm to reconstruct a d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5fcee0249d24932a9d9aba7e33184aae
https://doi.org/10.1007/978-3-030-01231-1_9
https://doi.org/10.1007/978-3-030-01231-1_9
Publikováno v:
IJCNN
This paper proposes the use of Stacked Denoising Autoencoder to predict the direction of movement of stock indexes based on the historical and volume data of the underlying stocks. The Stacked Denoising Autoencoder is a deep learning method widely us
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::87e49272f411131162382d5bf924db4c
https://doi.org/10.1109/ijcnn.2017.7966090
https://doi.org/10.1109/ijcnn.2017.7966090
Publikováno v:
IJCNN
Recognizing human faces is one of the most popular problems in the field of pattern recognition. Many approaches and methods have been tested and applied on the topic, especially neural networks. This paper proposed a new loss layer that can be repla
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fac1c6c4e414d8b3711237a19277c3fa
https://doi.org/10.1109/ijcnn.2017.7966089
https://doi.org/10.1109/ijcnn.2017.7966089
Autor:
Yuk Ying Chung, Seid Miad Zandavi, Henry Wing Fung Yeung, Wei-Chang Yeh, Weiming Zhi, Zhicheng Lu
Publikováno v:
Neural Information Processing ISBN: 9783319700922
ICONIP (4)
ICONIP (4)
This paper proposed a novel algorithm which named Randomized Particle Swarm Optimization (RPSO) to optimize HMM for human activity prediction. The experiments designed in this paper are the classification of human activity using two data sets. The fi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b618f47fc5eca820ab6b3269108ffcf5
https://doi.org/10.1007/978-3-319-70093-9_3
https://doi.org/10.1007/978-3-319-70093-9_3