Results 21 to 30 of about 83,262 (269)

Capsule Network with Shortcut Routing

open access: yesIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, 2021
8 pages, published at IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences E104.A(8)
Thanh Vu Dang   +3 more
openaire   +3 more sources

COVID-FACT: A Fully-Automated Capsule Network-Based Framework for Identification of COVID-19 Cases from Chest CT Scans

open access: yesFrontiers in Artificial Intelligence, 2021
The newly discovered Coronavirus Disease 2019 (COVID-19) has been globally spreading and causing hundreds of thousands of deaths around the world as of its first emergence in late 2019.
Shahin Heidarian   +11 more
doaj   +1 more source

Residual Capsule Network [PDF]

open access: yes2019 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
openaire   +1 more source

How to Accelerate Capsule Convolutions in Capsule Networks

open access: yesCoRR, 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
openaire   +2 more sources

Deep Tensor Capsule Network [PDF]

open access: yesIEEE 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
openaire   +2 more sources

CapsNets continuing the convolutional quest

open access: yesSciPost 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
doaj   +1 more source

Unraveling Capsule Biosynthesis and Signaling Networks in Cryptococcus neoformans

open access: yesMicrobiology 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
doaj   +1 more source

Path Capsule Networks

open access: yesNeural 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, Tomás Maul
openaire   +2 more sources

Chinese Short Text Entity Disambiguation Based on the Dual-Channel Hybrid Network

open access: yesIEEE 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
doaj   +1 more source

Towards Feasible Capsule Network for Vision Tasks

open access: yesApplied 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
doaj   +1 more source

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