Results 91 to 100 of about 204,781 (309)
Irregular Convolutional Neural Networks [PDF]
2017 4th IAPR Asian Conference on Pattern Recognition (ACPR), 2017 7 pages, 5 figures, 3 ...
Jiabin Ma +2 more
openaire +2 more sources
Deep convolutional neural networks for detection of rail surface defects [PDF]
, 2016 In this paper, we propose a deep convolutional neural network solution to the analysis of image data for the detection of rail surface defects. The images are obtained from many hours of automated video recordings.
Nunez, Alfredo (author) +9 more
core +1 more source
Advanced Functional Materials, EarlyView.This paper proposes a highly efficient ferroelectric artificial synapse device based on an oxide semiconductor and SnCl2‐inserted P(VDF‐TrFE) gate dielectric layer. This FeFET significantly improved the synaptic performance due to the ion‐dipole interaction.
Hyun‐Soo Kim +14 more
wiley +1 more source
Geometric Deep Learning for Protein–Protein Interaction Predictions
IEEE Access, 2022 This work introduces novel approaches, based on geometrical deep learning, for predicting protein–protein interactions. A dataset containing both interacting and non-interacting proteins is selected from the Negatome Database.
Gabriel St-Pierre Lemieux +3 more
doaj +1 more source
Understanding Convolutional Neural Networks
CoRR, 2016 Statistical Machine Learning Course Project at Carnegie Mellon ...
openaire +2 more sources
Convexified Convolutional Neural Networks
CoRR, 2016 We describe the class of convexified convolutional neural networks (CCNNs), which capture the parameter sharing of convolutional neural networks in a convex manner. By representing the nonlinear convolutional filters as vectors in a reproducing kernel Hilbert space, the CNN parameters can be represented as a low-rank matrix, which can be relaxed to ...
Yuchen Zhang 0002 +2 more
openaire +3 more sources
Clickbait Convolutional Neural Network [PDF]
Symmetry, 2018 With the development of online advertisements, clickbait spread wider and wider. Clickbait dissatisfies users because the article content does not match their expectation. Thus, clickbait detection has attracted more and more attention recently. Traditional clickbait-detection methods rely on heavy feature engineering and fail to distinguish clickbait ...
Hai-Tao Zheng 0002 +5 more
openaire +1 more source
Invertibility of convolutional generative networks from partial measurements [PDF]
, 2019 The problem of inverting generative neural networks (i.e., to recover the input latent code given partial network output), motivated by image inpainting, has recently been studied by a prior work that focused on fully-connected networks. In this work, we
Ayaz, Ulas +2 more
core
Advanced Healthcare Materials, EarlyView.Efficient recovery from traumatic or degenerative diseases is a great challenge, even after all the advancements in bone and cartilage regeneration. Machine learning (ML) algorithms have presented opportunities to enhance these aspects by accurately analyzing imaging data.
Maryam Kamaei +9 more
wiley +1 more source
Ferroelectric Quantum Dots for Retinomorphic In‐Sensor Computing
Advanced Materials, EarlyView.This work has provided a protocol for fabricating retinomorphic phototransistors by integrating ferroelectric ligands with quantum dots. The resulting device combines ferroelectricity, optical responsiveness, and low‐power operation to enable adaptive signal amplification and high recognition accuracy under low‐light conditions, while supporting ...
Tingyu Long +26 more
wiley +1 more source