Results 61 to 70 of about 288,791 (262)
Using Convolutional Neural Networks for Blocking Prediction in Elastic Optical Networks
Applied SciencesThis paper presents a study on connection-blocking prediction in Elastic Optical Networks (EONs) using Convolutional Neural Networks (CNNs). In EONs, connections are established and torn down dynamically to fulfill the instantaneous requirements of the ...
Farzaneh Nourmohammadi +3 more
doaj +1 more source
A Convolutional Neural Network model based on Neutrosophy for Noisy Speech Recognition
, 2019 Convolutional neural networks are sensitive to unknown noisy condition in the test phase and so their performance degrades for the noisy data classification task including noisy speech recognition.
Akbari, Ahmad +2 more
core +1 more source
Strategies in Jpeg Compression Using Convolutional Neural Network(Cnn) [PDF]
SSRN Electronic Journal, 2021 Interests in digital image processing are growing enormously in recent decades. As a result, different data compression techniques have been proposed which are concerned mostly with the minimization of information used for the representation of images. With the advances of deep neural networks, image compression can be achieved to a higher degree. This
openaire +2 more sources
Generative Models for Crystalline Materials
Advanced Materials, EarlyView.Generative machine learning models are increasingly used in crystalline materials design. This review outlines major generative approaches and assesses their strengths and limitations. It also examines how generative models can be adapted to practical applications, discusses key experimental considerations for evaluating generated structures, and ...
Houssam Metni +15 more
wiley +1 more source
Research on a Bearing Fault Diagnosis Method Based on a CNN-LSTM-GRU Model
MachinesIn view of the problem of the insufficient performance of deep learning models in time series prediction and poor comprehensive space–time feature extraction, this paper proposes a diagnostic method (CNN-LSTM-GRU) that integrates convolutional neural ...
Kaixu Han, Wenhao Wang, Jun Guo
doaj +1 more source
Particular object retrieval with integral max-pooling of CNN activations [PDF]
, 2016 Recently, image representation built upon Convolutional Neural Network (CNN) has been shown to provide effective descriptors for image search, outperforming pre-CNN features as short-vector representations.
Jégou, Hervé +2 more
core +1 more source
Advanced Materials Technologies, EarlyView.This review presents recent progress in vision‐augmented wearable interfaces that combine artificial vision, soft wearable sensors, and exoskeletal robots. Inspired by biological visual systems, these technologies enable multimodal perception and intelligent human–machine interaction.
Jihun Lee +4 more
wiley +1 more source
Rotational Objects Recognition and Angle Estimation via Kernel-Mapping CNN
IEEE Access, 2019 Convolutional neural network (CNN) has become the mainstream method in the field of image recognition for its excellent ability to feature extraction.
Yuanyuan Zhou +5 more
doaj +1 more source
Intelligent Prediction of Customer Churn with a Fused Attentional Deep Learning Model
Mathematics, 2022 In recent years, churn rates in industries such as finance have increased, and the cost of acquiring new users is more than five times the cost of retaining existing users. To improve the intelligent prediction accuracy of customer churn rate, artificial
Yunjie Liu +3 more
doaj +1 more source
Advanced Optical Materials, EarlyView.Solution‐processed MoS2 films with intrinsic sulfur‐vacancy traps are used to integrate light sensing and memory in a simple two‐terminal pixel. Successive optical pulses program persistent, multilevel conductance states, while oxygen exposure enables rapid erasure.
Jihyun Kim +8 more
wiley +1 more source