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Deep Phenotypic Cell Classification using Capsule Neural Network
2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021Recent developments in ultra-high-throughput microscopy have created a new generation of cell classification methodologies focused solely on image-based cell phenotypes. These image-based analyses enable morphological profiling and screening of thousands or even millions of single cells at a fraction of the cost. They have been shown to demonstrate the
Subhankar Chattoraj +5 more
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Network Traffic Classification Method Based on Improved Capsule Neural Network
2018 14th International Conference on Computational Intelligence and Security (CIS), 2018Convolution neural network (CNN) has achieved great performance in network traffic classification problem. However, it needs large-scale training set to achieve better classification performance while decreases the accuracy result in the case of the small dataset.
Fan Zhang, Yong Wang 0031, Miao Ye
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Implementing Capsule Neural Networks in Traffic Light Image Recognition
Proceedings of the 2020 ACM Southeast Conference, 2020Traffic Light Image Recognition is the problem of determining the signal of traffic lights within images taken by an autonomous vehicle. Currently, this is done by Convolutional Neural Network (CNN) machine learning systems. However, CNNs have issues managing positional information and routing data dynamically, so researchers have suggested the use of ...
Jing Selena He +3 more
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Learning Stance Classification with Recurrent Neural Capsule Network
2019Stance classification is a natural language processing (NLP) task to detect author’s stance when give a specific target and context, which can be applied in online debating forum, e.g., Twitter, Weibo, etc. In this paper, we present a novel target orientation recurrent neural capsule network, called TRNN-Capsule to solve the problem.
Lianjie Sun +4 more
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Hierarchical Capsule Based Neural Network Architecture for Sequence Labeling
2019 International Joint Conference on Neural Networks (IJCNN), 2019Sequence Labeling is one of the most prominent tasks in NLP. The traditional text classification models do not carry context from one sentence to another and hence may not perform well on these tasks. These models lack a hierarchical structure that can aid them in dissecting the input structure at different levels to allow flow of context between ...
Saurabh Srivastava +3 more
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Learning to Rank with Capsule Neural Networks
2022Anna Nesterenko, Anastasia Ianina
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Capsulated Graph Neural Network for Ubiquitylation Sites Prediction
2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2022Jie Chen 0027 +6 more
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A capsule-vectored neural network for hyperspectral image classification
Knowledge-Based Systems, 2023Xue Wang 0008 +4 more
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A non-local capsule neural network for hyperspectral remote sensing image classification
Remote Sensing Letters, 2021Runmin Lei, Chunju Zhang, Shihong Du
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Discriminating Earthquakes From Quarry Blasts Using Capsule Neural Network
IEEE Geoscience and Remote Sensing Letters, 2022Omar M Saad +2 more
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