Results 31 to 40 of about 324,009 (309)
2.5D MFFAU-Net: a convolutional neural network for kidney segmentation
BMC Medical Informatics and Decision Making, 2023 AbstractBackgroundKidney tumors have become increasingly prevalent among adults and are now considered one of the most common types of tumors. Accurate segmentation of kidney tumors can help physicians assess tumor complexity and aggressiveness before surgery.
Peng Sun +7 more
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LiteDEKR: End‐to‐end lite 2D human pose estimation network
IET Image Processing, 2023 The 2D human pose estimation plays an important role in human‐computer interaction and action recognition. Although the method based on high‐resolution network has superior performance, there is still room for improvement in terms of speed and ...
Xueqiang Lv +5 more
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C-Net: A reliable convolutional neural network for biomedical image classification [PDF]
Expert Systems with Applications, 2022 Cancers are the leading cause of death in many countries. Early diagnosis plays a crucial role in having proper treatment for this debilitating disease. The automated classification of the type of cancer is a challenging task since pathologists must examine a huge number of histopathological images to detect infinitesimal abnormalities.
Hosein Barzekar, Zeyun Yu
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Human stability assessment and fall detection based on dynamic descriptors
IET Image Processing, 2023 Fall detection systems use a number of different technologies to achieve their goals. This way, they contribute to better life conditions for the elderly community.
Jesús Gutiérrez +2 more
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A method for superfine pavement crack continuity detection based on topological loss
Electronics Letters, 2023 Deep convolutional neural networks have become a popular tool for the automatic detection of pavement cracks. Despite their widespread use, the models currently available tend to emphasize pixel‐level classification accuracy for cracks, often overlooking
Guohui Jia +4 more
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SA-Net: Shuffle Attention for Deep Convolutional Neural Networks [PDF]
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021 Attention mechanisms, which enable a neural network to accurately focus on all the relevant elements of the input, have become an essential component to improve the performance of deep neural networks. There are mainly two attention mechanisms widely used in computer vision studies, spatial attention and channel attention, which aim to capture the ...
Yu-Bin Yang, Qing-Long Zhang
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DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation [PDF]
2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS), 2020 Semantic image segmentation is the process of labeling each pixel of an image with its corresponding class. An encoder-decoder based approach, like U-Net and its variants, is a popular strategy for solving medical image segmentation tasks. To improve the performance of U-Net on various segmentation tasks, we propose a novel architecture called DoubleU ...
Jha, Debesh +4 more
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Deep Net Tree Structure for Balance of Capacity and Approximation Ability
Frontiers in Applied Mathematics and Statistics, 2019 Deep learning has been successfully used in various applications including image classification, natural language processing and game theory. The heart of deep learning is to adopt deep neural networks (deep nets for short) with certain structures to ...
Charles K. Chui +4 more
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High‐precision skeleton‐based human repetitive action counting
IET Computer Vision, 2023 A novel counting model is presented by the authors to estimate the number of repetitive actions in temporal 3D skeleton data. As per the authors’ knowledge, this is the first work of this kind using skeleton data for high‐precision repetitive action ...
Chengxian Li +3 more
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Fine-tuned convolutional neural nets for cardiac MRI acquisition plane recognition
Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2015 Ján Margeta +4 more
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