Zobrazeno 1 - 10
of 1 055
pro vyhledávání: '"attention decoder"'
Detecting and segmenting polyps is crucial for expediting the diagnosis of colon cancer. This is a challenging task due to the large variations of polyps in color, texture, and lighting conditions, along with subtle differences between the polyp and
Externí odkaz:
http://arxiv.org/abs/2403.18180
Publikováno v:
In Biomedical Signal Processing and Control July 2024 93
Publikováno v:
In Engineering Science and Technology, an International Journal June 2024 54
Publikováno v:
Engineering Science and Technology, an International Journal, Vol 54, Iss , Pp 101705- (2024)
Calculating depth using just one image is a crucial issue since it has applications in numerous computer vision domains. Although some recent works directly obtain the depth map through some complex and powerful networks, we want to combine the encod
Externí odkaz:
https://doaj.org/article/f9411823c2c94e6e9547ebb45b765bdd
Automatic medical image segmentation based on Computed Tomography (CT) has been widely applied for computer-aided surgery as a prerequisite. With the development of deep learning technologies, deep convolutional neural networks (DCNNs) have shown rob
Externí odkaz:
http://arxiv.org/abs/2104.03715
The Transformer has shown impressive performance in automatic speech recognition. It uses the encoder-decoder structure with self-attention to learn the relationship between the high-level representation of the source inputs and embedding of the targ
Externí odkaz:
http://arxiv.org/abs/2006.10407
Publikováno v:
In Engineering Applications of Artificial Intelligence September 2022 114
Segmentation algorithms for medical images are widely studied for various clinical and research purposes. In this paper, we propose a new and efficient method for medical image segmentation under noisy labels. The method operates under a deep learnin
Externí odkaz:
http://arxiv.org/abs/2009.12873
Publikováno v:
In Engineering Applications of Artificial Intelligence June 2022 112
Publikováno v:
In Neural Networks May 2021 137:188-199