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Overview of Capsule Neural Networks
網際網路技術學刊, 2022<p>As a vector transmission network structure, the capsule neural network has been one of the research hotspots in deep learning since it was proposed in 2017. In this paper, the latest research progress of capsule networks is analyzed and summarized. Firstly, we summarize the shortcomings of convolutional neural networks
Zengguo Sun Zengguo Sun +4 more
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Steady Flow Approximation using Capsule Neural Networks
2020 IEEE Sixth International Conference on Multimedia Big Data (BigMM), 2020CFD (Computational Fluid Dynamics) solvers have been very popular for fluid flow simulation which has been proved to be imperative to solve modern problems relating to analysis, design, and optimization in the field of aerodynamics. Nevertheless, CFD simulations are usually memory intensive and computationally demanding, iterative time-consuming ...
Abhijit Uday Kurtakoti +1 more
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Improving Training time in Capsule Neural Network
2021 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA), 2021Chiadika Electrical & Computer Engr Mathematics department Electrical & Computer Engr Brunel University, Seoul National University Brunel University, London, United Kingded the Attention Routing CapsuleNet (AR CapsNet) as proposed by Jaewoong Choi et al. in Attention Routing between Capsules. The AR-CapsNet is an enhanced version of CapsNet which, uses
Onyeachonam Dominic-Mario Chiadika +2 more
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Personality Recognition in Conversations using Capsule Neural Networks
IEEE/WIC/ACM International Conference on Web Intelligence, 2019Automatic identification of personality in conversations has many applications in natural language processing, such as community role identification (e.g., group leader) in online social media conversations as well as meeting transcripts. Conversation utterances provide a lot of information about the parties involved in a conversation such as cues to ...
Esteban Andrés Ríssola +2 more
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Parallel Capsule Neural Networks for Sound Event Detection
2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2019In this work, we propose a sound event detection system based on a parallel capsule neural network. The system takes advantage of the capability of capsule neural networks in the detection of overlapping objects. It further develops a parallel architecture and uses the kernel design of different shapes and sizes to effectively utilize the feature ...
Kai-Wen Liang +2 more
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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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