Zobrazeno 1 - 10
of 32
pro vyhledávání: '"Mofei Song"'
Autor:
Mofei Song, Qi Guo
Publikováno v:
Journal of Cloud Computing: Advances, Systems and Applications, Vol 11, Iss 1, Pp 1-16 (2022)
Abstract 3D object recognition has great research and application value in the fields of automatic drive, virtual reality, and commercial manufacturing. Although various deep models have been exploited and achieved remarkable results for 3D object re
Externí odkaz:
https://doaj.org/article/b38ba9fd143e42bebb00ef4b71052f21
Publikováno v:
Journal of Cloud Computing: Advances, Systems and Applications, Vol 10, Iss 1, Pp 1-14 (2021)
Abstract The visibility estimation of the environment has great research and application value in the fields of production. To estimate the visibility, we can utilize the camera to obtain some images as evidence. However, the camera only solves the i
Externí odkaz:
https://doaj.org/article/86f6cac0aac94860b6d397e265514e9b
Autor:
Mofei Song
Publikováno v:
Entropy, Vol 22, Iss 11, p 1314 (2020)
Currently, deep learning has shown state-of-the-art performance in image classification with pre-defined taxonomy. However, in a more real-world scenario, different users usually have different classification intents given an image collection. To sat
Externí odkaz:
https://doaj.org/article/dd07572e5f0949a2bbab28622388fb1e
Publikováno v:
Computers, Materials & Continua. 75:197-217
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6a5dbd9455bfe0b32583a54e57e06841
https://doi.org/10.32604/cmc.2023.036365
https://doi.org/10.32604/cmc.2023.036365
Publikováno v:
IEEE Transactions on Circuits and Systems for Video Technology. 32:5453-5466
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::62ab282a528f5f5fc20077da47fbe99a
https://doi.org/10.1109/tcsvt.2022.3150923
https://doi.org/10.1109/tcsvt.2022.3150923
Publikováno v:
Journal of Cloud Computing: Advances, Systems and Applications, Vol 10, Iss 1, Pp 1-14 (2021)
The visibility estimation of the environment has great research and application value in the fields of production. To estimate the visibility, we can utilize the camera to obtain some images as evidence. However, the camera only solves the image acqu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::990484a3fe6ea1496d4cba27964cc629
https://doaj.org/article/86f6cac0aac94860b6d397e265514e9b
https://doaj.org/article/86f6cac0aac94860b6d397e265514e9b
In this paper, we present a novel model for simultaneous stable co-saliency detection (CoSOD) and object co-segmentation (CoSEG). To detect co-saliency (segmentation) accurately, the core problem is to well model inter-image relations between an imag
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a70224470f1fec81417318926174b749
http://arxiv.org/abs/2209.12138
http://arxiv.org/abs/2209.12138
Publikováno v:
Computer Graphics Forum. 39:279-289
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2eb59699b24b8334761720cb696adaa1
https://doi.org/10.1111/cgf.14144
https://doi.org/10.1111/cgf.14144
Autor:
Mofei Song
Publikováno v:
The Visual Computer. 37:497-514
To efficiently and flexibly classify 3D shape in a user-adaptive way, this paper proposes a novel interactive system by incorporating active learning, online learning and user intervention. Given a shape collection, our system iteratively alternates
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3bc68d47089a5f60e6f5e1ff08df6680
https://doi.org/10.1007/s00371-020-01819-3
https://doi.org/10.1007/s00371-020-01819-3
Publikováno v:
2021 IEEE/CVF International Conference on Computer Vision (ICCV).
Aiming at discovering and locating most distinctive objects from visual scenes, salient object detection (SOD) plays an essential role in various computer vision systems. Coming to the era of high resolution, SOD methods are facing new challenges. Th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::46a0a7fb7cf7d6bd13e89344b51ae0ac
https://doi.org/10.1109/iccv48922.2021.00356
https://doi.org/10.1109/iccv48922.2021.00356