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International Journal of Machine Learning and Cybernetics, 2021
The capsule network (CapsNet) is a novel network model that can learn spatial information in images. However, the performance of CapsNet on complex datasets (such as CIFAR10) is limited and it requires a large number of parameters. These disadvantages make CapsNet less useful, especially in some resource-constrained devices.
Kun Sun +3 more
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The capsule network (CapsNet) is a novel network model that can learn spatial information in images. However, the performance of CapsNet on complex datasets (such as CIFAR10) is limited and it requires a large number of parameters. These disadvantages make CapsNet less useful, especially in some resource-constrained devices.
Kun Sun +3 more
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Group Feedback Capsule Network
IEEE Transactions on Image Processing, 2020In capsule networks (CapsNets), the capsule is made up of collections of neurons. Their adjacent capsule layers are connected using routing-by-agreement mechanisms in an unsupervised way. The routing-by-agreement mechanisms have two main drawbacks: a) too many parameters and high computation complexity; b) the cluster distribution assumptions of these ...
Xinpeng Ding +5 more
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Capsule Networks with Routing Annealing
2021Capsule Networks overcome some shortcomings of convolutional neural networks organizing neurons into groups of capsules. Capsule layers are dynamically connected by means of an iterative routing mechanism, which models the connection strengths between capsules from different layers.
Riccardo Renzulli +3 more
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A brief survey on Capsule Network
2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), 2020Capsule networks(CapsNets) are new kinds of network representation in deep learning. They are proposed to overcome the shortcomings of convolutional neural networks(CNNs). CNNs do not consider the important spatial level correlation between simple and complex objects. Besides, the pooling operations lose too much spatial information.
Ruiyang Shi, Lingfeng Niu
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MapReduce-based Capsule Networks
2019 Sixth International Conference on Social Networks Analysis, Management and Security (SNAMS), 2019Currently, artificial intelligence technology is attracting much attention, and image processing field is also making remarkable progress in recognition rate through CNN models. Furthermore, Capsule Network which is flexible in changing pose of image is being studied in various fields by improving disadvantage of Pooling Layer of CNN model.
Sun-Jin Park, Ho-Hyun Park
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CNN to Capsule Network Transformation
2020 Digital Image Computing: Techniques and Applications (DICTA), 2020Capsule Network has been recently proposed which outperforms CNN in specific tasks. Due to the network architecture differences between Capsule Network and CNN, Capsule Network could not use transfer learning which is very frequently used in CNN. In this paper, we propose a transfer learning method which can easily transfer CNN to Capsule Network.
Takumi Sato, Kazuhiro Hotta
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2019
Multi-view learning attempts to generate a model with a better performance by exploiting information among multi-view data. Most existing approaches only focus on either consistency or complementarity principle, and learn representations (or features) of the multi-view data. In this paper, to utilize both complementarity and consistency simultaneously,
Jianwei Liu 0006 +5 more
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Multi-view learning attempts to generate a model with a better performance by exploiting information among multi-view data. Most existing approaches only focus on either consistency or complementarity principle, and learn representations (or features) of the multi-view data. In this paper, to utilize both complementarity and consistency simultaneously,
Jianwei Liu 0006 +5 more
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Narrowing Attention in Capsule Networks
2022 26th International Conference on Pattern Recognition (ICPR), 2022Sebastian Thiele, Benjamin Risse
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2004
In this text, the author tries to formulate the 'laws' of capsularisation: technological mechanisms, economical processes like dualisation, sociological processes like exclusion etcetera. One of the main points of the text is that the network is not only creating a world of interconnection, but also a world of separation. No network without capsules.
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In this text, the author tries to formulate the 'laws' of capsularisation: technological mechanisms, economical processes like dualisation, sociological processes like exclusion etcetera. One of the main points of the text is that the network is not only creating a world of interconnection, but also a world of separation. No network without capsules.
openaire +1 more source