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How to Accelerate Capsule Convolutions in Capsule Networks
CoRR, 2021 How to improve the efficiency of routing procedures in CapsNets has been studied a lot. However, the efficiency of capsule convolutions has largely been neglected. Capsule convolution, which uses capsules rather than neurons as the basic computation unit, makes it incompatible with current deep learning frameworks' optimization solution.
Zhenhua Chen 0003 +3 more
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Residual Capsule Network [PDF]
2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), 2019 Convolution Neural Network (CNN) has been the most influential innovations in the filed of Computer Vision. CNN have shown a substantial improvement in the field of Machine Learning. But they do come with their own set of drawbacks - CNN need a large dataset, hyperparameter tuning is nontrivial and importantly, they lose all the internal information ...
Sree Bala Shruthi Bhamidi +1 more
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CapsNets continuing the convolutional quest
SciPost Physics, 2020 Capsule networks are ideal tools to combine event-level and subjet information at the LHC. After benchmarking our capsule network against standard convolutional networks, we show how multi-class capsules extract a resonance decaying to top quarks from
Sascha Diefenbacher, Hermann Frost, Gregor Kasieczka, Tilman Plehn, Jennifer M. Thompson
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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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Unraveling Capsule Biosynthesis and Signaling Networks in Cryptococcus neoformans
Microbiology Spectrum, 2022 The polysaccharide capsule of Cryptococcus neoformans—an opportunistic basidiomycete pathogen and the major etiological agent of fungal meningoencephalitis—is a key virulence factor that prevents its phagocytosis by host innate immune cells. However, the
Eun-Ha Jang +3 more
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Chinese Short Text Entity Disambiguation Based on the Dual-Channel Hybrid Network
IEEE Access, 2020 Entity disambiguation refers to the accurate inference of the real mention of an entity with the same name according to the context. Most existing studies focused on long texts, for short texts, the performance has been unsatisfactory due to sparsity. In
Liting Jiang +4 more
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Breaking CAPTCHA with Capsule Networks
Neural Networks, 2022 Convolutional Neural Networks have achieved state-of-the-art performance in image classification. Their lack of ability to recognise the spatial relationship between features, however, leads to misclassification of the variants of the same image. Capsule Networks were introduced to address this issue by incorporating the spatial information of image ...
Ionela Georgiana Mocanu +2 more
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Neural Processing Letters, 2020 Capsule network (CapsNet) was introduced as an enhancement over convolutional neural networks, supplementing the latter's invariance properties with equivariance through pose estimation. CapsNet achieved a very decent performance with a shallow architecture and a significant reduction in parameters count.
Mohammed Amer 0001, Tomas Maul
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Pushing the Limits of Capsule Networks
CoRR, 2021 Convolutional neural networks use pooling and other downscaling operations to maintain translational invariance for detection of features, but in their architecture they do not explicitly maintain a representation of the locations of the features relative to each other.
Prem Nair, Rohan Doshi, Stefan Keselj
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Towards Feasible Capsule Network for Vision Tasks
Applied Sciences, 2023 Capsule networks exhibit the potential to enhance computer vision tasks through their utilization of equivariance for capturing spatial relationships.
Dang Thanh Vu +3 more
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