Zobrazeno 1 - 10
of 519
pro vyhledávání: '"CHEN Yingyi"'
Publikováno v:
智慧农业, Vol 5, Iss 4, Pp 137-149 (2023)
[Objective]Intelligent feeding methods are significant for improving breeding efficiency and reducing water quality pollution in current aquaculture. Feeding image segmentation of fish schools is a critical step in extracting the distribution charact
Externí odkaz:
https://doaj.org/article/f22f9cd1f5d34e6dafce59254c8a39ce
Publikováno v:
Heliyon, Vol 9, Iss 6, Pp e17332- (2023)
Image motion deblurring is a crucial technology in computer vision that has gained significant attention attracted by its outstanding ability for accurate acquisition of motion image information, processing and intelligent decision making, etc. Motio
Externí odkaz:
https://doaj.org/article/aa08e865b6ad40a09ce00013b00b5037
Publikováno v:
智慧农业, Vol 4, Iss 1, Pp 130-139 (2022)
Convolutional neural network models have different advantages and disadvantages, it is becoming more and more difficult to select an appropriate convolutional neural network model in an actual fish identification project. The identification of underw
Externí odkaz:
https://doaj.org/article/6ee1de60dd7f467384128fea694724ad
Autor:
Tao, Qinghua, Tonin, Francesco, Lambert, Alex, Chen, Yingyi, Patrinos, Panagiotis, Suykens, Johan A. K.
Publikováno v:
the 41st International Conference on Machine Learning (ICML), 2024
In contrast with Mercer kernel-based approaches as used e.g., in Kernel Principal Component Analysis (KPCA), it was previously shown that Singular Value Decomposition (SVD) inherently relates to asymmetric kernels and Asymmetric Kernel Singular Value
Externí odkaz:
http://arxiv.org/abs/2406.08748
In this paper, we revisit techniques for uncertainty estimation within deep neural networks and consolidate a suite of techniques to enhance their reliability. Our investigation reveals that an integrated application of diverse techniques--spanning m
Externí odkaz:
http://arxiv.org/abs/2403.00543
While the great capability of Transformers significantly boosts prediction accuracy, it could also yield overconfident predictions and require calibrated uncertainty estimation, which can be commonly tackled by Gaussian processes (GPs). Existing work
Externí odkaz:
http://arxiv.org/abs/2402.01476
Recently, a new line of works has emerged to understand and improve self-attention in Transformers by treating it as a kernel machine. However, existing works apply the methods for symmetric kernels to the asymmetric self-attention, resulting in a no
Externí odkaz:
http://arxiv.org/abs/2305.19798
The success of Vision Transformer (ViT) in various computer vision tasks has promoted the ever-increasing prevalence of this convolution-free network. The fact that ViT works on image patches makes it potentially relevant to the problem of jigsaw puz
Externí odkaz:
http://arxiv.org/abs/2207.11971
Supervised learning can be viewed as distilling relevant information from input data into feature representations. This process becomes difficult when supervision is noisy as the distilled information might not be relevant. In fact, recent research s
Externí odkaz:
http://arxiv.org/abs/2206.13140
Publikováno v:
In Aquacultural Engineering November 2024 107