Results 31 to 40 of about 102,675 (264)

CNN 101: Interactive Visual Learning for Convolutional Neural Networks [PDF]

Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, 2020
The success of deep learning solving previously-thought hard problems has inspired many non-experts to learn and understand this exciting technology. However, it is often challenging for learners to take the first steps due to the complexity of deep learning models.
Zijie J. Wang, Robert Turko, Omar Shaikh, Haekyu Park, Nilaksh Das, Fred Hohman, Minsuk Kahng, Duen Horng Chau   +7 more
openaire   +2 more sources

Sub-Millisecond Phase Retrieval for Phase-Diversity Wavefront Sensor

Sensors, 2020
We propose a convolutional neural network (CNN) based method, namely phase diversity convolutional neural network (PD-CNN) for the speed acceleration of phase-diversity wavefront sensing.
Yu Wu, Youming Guo, Hua Bao, Changhui Rao   +3 more
doaj   +1 more source

Improved Convolutional Neural Image Recognition Algorithm based on LeNet-5

Journal of Computer Networks and Communications, 2022
Convolutional neural network (CNN) is a very important method in deep learning, which solves many complex pattern recognition problems. Fruitful results have been achieved in image recognition, speech recognition, and natural language processing ...
Lijie Zhou, Weihai Yu
doaj   +1 more source

Convolutional neural networks: an overview and application in radiology

Insights into Imaging, 2018
Convolutional neural network (CNN), a class of artificial neural networks that has become dominant in various computer vision tasks, is attracting interest across a variety of domains, including radiology.
Rikiya Yamashita, Mizuho Nishio, Richard Kinh Gian Do, Kaori Togashi   +3 more
doaj   +1 more source

Research on epileptic EEG recognition based on improved residual networks of 1-D CNN and indRNN

BMC Medical Informatics and Decision Making, 2021
Background Epilepsy is one of the diseases of the nervous system, which has a large population in the world. Traditional diagnosis methods mostly depended on the professional neurologists’ reading of the electroencephalogram (EEG), which was time ...
Mengnan Ma, Yinlin Cheng, Xiaoyan Wei, Ziyi Chen, Yi Zhou   +4 more
doaj   +1 more source

Optimasi Convolutional Neural Network dan K-Fold Cross Validation pada Sistem Klasifikasi Glaukoma

Jurnal Elkomika, 2022
ABSTRAK Pada penelitian ini dilakukan perancangan arsitektur Convolutional Neural Network (CNN) yang terdiri dari 5 layer konvolusi dan 1-fully connected layer untuk mengklasifikasikan citra fundus kedalam kondisi normal, early, moderate, deep, dan ...
YUNENDAH NUR FUADAH, IBNU DAWAN UBAIDULLAH, NUR IBRAHIM, FAUZI FRAHMA TALININGSING, NIDAAN KHOFIYA SY, MUHAMMAD ADNAN PRAMUDITHO   +5 more
doaj   +1 more source

A lightweight multi-path convolutional neural network architecture using optimal features selection for multiclass classification of brain tumor using magnetic resonance images

Results in Engineering
Brain tumor diagnosis requires precision due to the high mortality rate associated with the growth of abnormal cells in the brain. Early disease identification, improved survival rates, and less reliance on professional MRI analysis is possible with ...
Amreen Batool, Yung-Cheol Byun
doaj   +1 more source

SPEAKER IDENTIFICATION SYSTEM USING AUDIO SIGNAL AND DEEP LEARNING METHOD [PDF]

Proceedings on Engineering Sciences
Automatic Speaker Identification (ASI) does not result in high accuracy, so it is essential to develop a highly accurate Speaker Identification (SI) system. Artificial Intelligence has shown remarkable improvement in the development of such systems using
Neelam Nehra , Pardeep Sangwan , Neelu Trivedi   +2 more
doaj   +1 more source

Short Text Aspect-Based Sentiment Analysis Based on CNN + BiGRU

Applied Sciences, 2022
This paper describes the construction a short-text aspect-based sentiment analysis method based on Convolutional Neural Network (CNN) and Bidirectional Gating Recurrent Unit (BiGRU).
Ziwen Gao, Zhiyi Li, Jiaying Luo, Xiaolin Li   +3 more
doaj   +1 more source

Nondestructive prediction of physicochemical properties of kimchi sauce with artificial and convolutional neural networks

International Journal of Food Properties, 2023
This study presents a comparison of prediction performances by an artificial neural network (ANN), well-known deep convolutional neural network (D-CNN) models, and four proposed shallow convolutional neural network (S-CNN) models to forecast three key ...
Hae-Il Yang, Sung-Gi Min, Hye-Young Seo, Seong Youl Lee, Ji-Hee Yang, Mi-Ai Lee, Sung-Hee Park, Jong-Bang Eun, Young Bae Chung   +8 more
doaj   +1 more source