Results 41 to 50 of about 288,791 (262)
Deep Learning Approaches on Defect Detection in High Resolution Aerial Images of Insulators
Sensors, 2021 By detecting the defect location in high-resolution insulator images collected by unmanned aerial vehicle (UAV) in various environments, the occurrence of power failure can be timely detected and the caused economic loss can be reduced.
Qiaodi Wen +4 more
doaj +1 more source
Topical Behavior Prediction from Massive Logs
, 2017 In this paper, we study the topical behavior in a large scale. We use the network logs where each entry contains the entity ID, the timestamp, and the meta data about the activity.
Su, Shih-Chieh
core +1 more source
Structural Damage Detection Based on One-Dimensional Convolutional Neural Network
Applied Sciences, 2022 This paper proposes a structural damage detection method based on one-dimensional convolutional neural network (CNN). The method can automatically extract features from data to detect structural damage.
Zhigang Xue, Chenxu Xu, Dongdong Wen
doaj +1 more source
Improving Efficiency in Convolutional Neural Network with Multilinear Filters
, 2017 The excellent performance of deep neural networks has enabled us to solve several automatization problems, opening an era of autonomous devices. However, current deep net architectures are heavy with millions of parameters and require billions of ...
Gabbouj, Moncef +2 more
core +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Peripheral neuropathies contribute to patient disability but may be diagnosed late or missed altogether due to late referral, limitation of current diagnostic methods and lack of specialized testing facilities. To address this clinical gap, we developed NeuropathAI, an interpretable deep learning–based multiclass classification ...
Chaima Ben Rabah +7 more
wiley +1 more source
CNN-Siam: multimodal siamese CNN-based deep learning approach for drug‒drug interaction prediction
BMC Bioinformatics, 2023 Background Drug‒drug interactions (DDIs) are reactions between two or more drugs, i.e., possible situations that occur when two or more drugs are used simultaneously. DDIs act as an important link in both drug development and clinical treatment. Since it
Zihao Yang +5 more
doaj +1 more source
Adverse Drug Reaction Classification With Deep Neural Networks [PDF]
, 2016 We study the problem of detecting sentences describing adverse drug reactions (ADRs) and frame the problem as binary classification. We investigate different neural network (NN) architectures for ADR classification.
He, Yulan +3 more
core +1 more source
Tube Convolutional Neural Network (T-CNN) for Action Detection in Videos
, 2017 Deep learning has been demonstrated to achieve excellent results for image classification and object detection. However, the impact of deep learning on video analysis (e.g.
Chen, Chen, Hou, Rui, Shah, Mubarak
core +1 more source
Advanced Functional Materials, EarlyView.This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee +17 more
wiley +1 more source
Learning text representation using recurrent convolutional neural network with highway layers [PDF]
, 2016 Recently, the rapid development of word embedding and neural networks has brought new inspiration to various NLP and IR tasks. In this paper, we describe a staged hybrid model combining Recurrent Convolutional Neural Networks (RCNN) with highway layers ...
Luo, Rui +3 more
core +1 more source