Results 51 to 60 of about 21,605 (294)
Artificial Intelligence in Colon Capsule Endoscopy—A Systematic Review
Diagnostics, 2022 Background and aims: The applicability of colon capsule endoscopy in daily practice is limited by the accompanying labor-intensive reviewing time and the risk of inter-observer variability.
Sarah Moen +3 more
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A Unified Framework of Deep Neural Networks by Capsules [PDF]
, 2019 With the growth of deep learning, how to describe deep neural networks unifiedly is becoming an important issue. We first formalize neural networks mathematically with their directed graph representations, and prove a generation theorem about the induced networks of connected directed acyclic graphs.
Yujian Li, Chuanhui Shan
openaire +2 more sources
Sensors, 2021 Compared to time-consuming and unreliable manual analysis, intelligent fault diagnosis techniques using deep learning models can improve the accuracy of intelligent fault diagnosis with their multi-layer nonlinear mapping capabilities.
Bin Han +3 more
doaj +1 more source
ABPCaps: A Novel Capsule Network-Based Method for the Prediction of Antibacterial Peptides
Applied Sciences, 2023 The emergence of drug resistance among pathogens has become a major challenge to human health on a global scale. Among them, antibiotic resistance is already a critical issue, and finding new therapeutic agents to address this problem is therefore urgent.
Lantian Yao +8 more
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Optimization of the closed-loop controller of a discontinuous capsule drive using a neural network
, 2022 Research data connected to the following paper: Optimization of the closed-loop controller of a discontinuous capsule drive using a neural network.In this paper, construction of a neural-network based, closed-loop control of a discontinuous capsule drive
Zarychta, S (via Mendeley Data)
core +1 more source
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2022 Locomotion mode recognition has been shown to substantially contribute to the precise control of robotic lower-limb prostheses under different walking conditions. In this study, we proposed a temporal convolutional capsule network (TCCN) which integrates
Yanggang Feng +4 more
doaj +1 more source
Polyphonic Sound Event Detection by Using Capsule Neural Networks [PDF]
IEEE Journal of Selected Topics in Signal Processing, 2019 Artificial sound event detection (SED) has the aim to mimic the human ability to perceive and understand what is happening in the surroundings. Nowadays, Deep Learning offers valuable techniques for this goal such as Convolutional Neural Networks (CNNs).
Fabio Vesperini +3 more
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Structural-parametric Synthesis of Capsule Neural Networks
Electronics and Control Systems, 2023 This work is dedicated to the structural-parametric synthesis of capsule neural networks. A methodology for structural-parametric synthesis of capsule neural networks has been developed, which includes the following algorithms: determining the most influential parameters of the capsule neural network, a hybrid machine learning algorithm.
Victor Sineglazov, Denys Kudriev
openaire +1 more source
Multi-Kernel Capsule Network for Schizophrenia Identification [PDF]
, 2020 Schizophrenia seriously affects the quality of life. To date, both simple (e.g., linear discriminant analysis) and complex (e.g., deep neural network) machine learning methods have been utilized to identify schizophrenia based on functional connectivity ...
Li, Junhua +3 more
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Research on Lane Occupancy Rate Forecasting Based on the Capsule Network
IEEE Access, 2020 This paper proposes a hybrid lane occupancy rate prediction model called 2LayersCapsNet, which combines the improved capsule network and convolutional neural networks (CNNs). The model uses CNNs to mine the spatial-temporal correlation characteristics of
Ran Tian +3 more
doaj +1 more source