Results 21 to 30 of about 53,606 (313)
Continuous speech recognition by convolutional neural networks
工程科学学报, 2015 Convolutional neural networks (CNNs), which show success in achieving translation invariance for many image processing tasks, were investigated for continuous speech recognition.
ZHANG Qing-qing +3 more
doaj +1 more source
Attention-Based Convolutional LSTM for Describing Video
IEEE Access, 2020 Video description technique has been widely used in the computer community for many applications. The typical approaches are mainly based on the encode-decode framework: the fixed-length video representation vectors are extracted by the encoder using the
Zhongyu Liu +4 more
doaj +1 more source
Optimizing the Energy Consumption of Spiking Neural Networks for Neuromorphic Applications
Frontiers in Neuroscience, 2020 In the last few years, spiking neural networks (SNNs) have been demonstrated to perform on par with regular convolutional neural networks. Several works have proposed methods to convert a pre-trained CNN to a Spiking CNN without a significant sacrifice ...
Martino Sorbaro +4 more
doaj +1 more source
A Comprehensive Review on the Application of 3D Convolutional Neural Networks in Medical Imaging
Engineering Proceedings, 2023 Convolutional Neural Networks (CNNs) are kinds of deep learning models that were created primarily for processing and evaluating visual input, which makes them extremely applicable in the field of medical imaging.
Satyam Tiwari +5 more
doaj +1 more source
CNN Explainer: Learning Convolutional Neural Networks with Interactive Visualization [PDF]
IEEE Transactions on Visualization and Computer Graphics, 2021 11 pages, 14 figures, to be presented at IEEE VIS 2020. For a demo video, see https://youtu.be/HnWIHWFbuUQ . For a live demo, visit https://poloclub.github.io/cnn-explainer/
Wang, Zijie J. +7 more
openaire +3 more sources
Convolutional Neural Network (CNN): A comprehensive overview
International Journal of Multidisciplinary Research and Growth Evaluation, 2022 Convolutional neural network (CNN), a class of artificial neural network (ANN) is attracting interests of researchers in all research domain. CNN was invented for computer vision. They have also shown to be useful for semantic parsing, sentence modeling and other natural language processing related tasks. Here in this paper we discuss the basics of CNN
openaire +1 more source
A Review of Convolutional Neural Network Development in Computer Vision
EAI Endorsed Transactions on Internet of Things, 2022 Convolutional neural networks have made admirable progress in computer vision. As a fast-growing computer field, CNNs are one of the classical and widely used network structures. The Internet of Things (IoT) has gotten a lot of attention in recent years.
Hang Zhang
doaj +1 more source
Pneumonia Detection using Convolutional Neural Network (CNN)
International Journal of Advanced Research in Science, Communication and Technology, 2023 Pneumonia Is A Dangerous And Sometimes Fatal Disease That Primarily Affects Older People. Early Diagnosis Of Pneumonia Is Key To Saving Many Lives. This Study Attempted To Identify And Classify Patients With Pneumonia Based On Chest X-Rays. The Diagnostics Above Were Performed Using A Convolutional Neural Network, Which Was Built From The Ground Up And
null Prof. Praveen Thummalakunta +4 more
openaire +1 more source
Remote Sensing, 2020 The accurate acquisition of water information from remote sensing images has become important in water resources monitoring and protections, and flooding disaster assessment.
Guojie Wang +3 more
doaj +1 more source
Quantum convolutional neural networks for high energy physics data analysis
Physical Review Research, 2022 This paper presents a quantum convolutional neural network (QCNN) for the classification of high energy physics events. The proposed model is tested using a simulated dataset from the Deep Underground Neutrino Experiment.
Samuel Yen-Chi Chen +4 more
doaj +1 more source