Results 31 to 40 of about 29,311 (260)
Analysis of Video Retinal Angiography With Deep Learning and Eulerian Magnification
Frontiers in Computer Science, 2020 Objective: The aim of this research is to present a novel computer-aided decision support tool in analyzing, quantifying, and evaluating the retinal blood vessel structure from fluorescein angiogram (FA) videos.Methods: The proposed method consists of ...
Sumit Laha +6 more
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Multi-channel capsule network ensemble for plant disease detection
SN Applied Sciences, 2021 This study presents a new deep learning approach based on capsule networks and ensemble learning for the detection of plant diseases. The developed method is called as multi-channel capsule network ensemble. The main innovation behind the proposed method
Musa Peker
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Capsule Networks as Generative Models
, 2023 Accepted at the 3rd International Workshop on Active Inference, 19th Sept 2022, Grenoble; This version: added reference, corrected typographical error; final submitted ...
Kiefer, Alex B. +3 more
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Remote Sensing, 2019 Capsule networks can be considered to be the next era of deep learning and have recently shown their advantages in supervised classification. Instead of using scalar values to represent features, the capsule networks use vectors to represent features ...
Kaiqiang Zhu +4 more
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Deep Tensor Capsule Network [PDF]
IEEE Access, 2020 La red de cápsulas es un modelo prometedor en visión artificial. Ha logrado excelentes resultados en conjuntos de datos simples como MNIST, pero el rendimiento se deteriora a medida que los datos se complican. Para abordar este problema, proponemos una red de cápsulas profundas en este documento.
Kun Sun +3 more
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Arterial Spin Labeling Image Synthesis From Structural MRI Using Improved Capsule-Based Networks
IEEE Access, 2020 Medical image synthesis receives much popularity in recent years, and ample medical images can be synthesized by diverse deep learning models to alleviate the problem of lack of data in many medical imaging utilizations.
Wei Huang +4 more
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Efficient-CapsNet: capsule network with self-attention routing
Scientific Reports, 2021 Deep convolutional neural networks, assisted by architectural design strategies, make extensive use of data augmentation techniques and layers with a high number of feature maps to embed object transformations.
Vittorio Mazzia +2 more
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Intelligent Classification of Japonica Rice Growth Duration (GD) Based on CapsNets
Plants, 2022 Rice cultivation in cold regions of China is mainly distributed in Heilongjiang Province, where the growing season of rice is susceptible to low temperature and cold damage.
Xin Zhao +5 more
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Machines, 2022 As scalar neurons of traditional neural networks promote dimension reduction caused by pooling, it is a difficult task to extract the high-dimensional spatial features and long-term correlation of pure signals from the noisy vibration signal.
Youming Wang, Gongqing Cao, Jiali Han
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An Improved Capsule Network Based on Capsule Filter Routing [PDF]
IEEE Access, 2021 Capsule network (CapsNet) is a novel type of network that can retain spatial information, because each capsule can integrate more information than scalar-output features. However, the CapsNet learns all the features in the input image due to the lack of pooling operation, and there is no connection between different layers in the multi-layer network ...
Wei Wang +3 more
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