Results 101 to 110 of about 73,468 (309)

Detecting Alzheimer’s disease and brain tumors using machine learning and convolutional neural networks (CNNs) [PDF]

This white paper presents a systematic study and proposes a novel solution for detecting Alzheimer's disease and brain tumors using machine learning (ML) and Convolutional Neural Networks (CNNs).
Nag Shivani Puram
core   +1 more source

3D Discrete Matrix-Product Operation and Its Generalization

Journal of Function Spaces
Two-dimensional (2D) discrete matrix-product operation (DMPO) and its corresponding matrix-product neural networks (MPNNs) are the substitutions of 2D discrete convolutional operation and its corresponding convolutional neural networks (CNNs ...
Chuanhui Shan, Hu Li, Chao Han
doaj   +1 more source

Single Image Super-Resolution Based on Multi-Scale Competitive Convolutional Neural Network

Sensors, 2018
Deep convolutional neural networks (CNNs) are successful in single-image super-resolution. Traditional CNNs are limited to exploit multi-scale contextual information for image reconstruction due to the fixed convolutional kernel in their building modules.
Xiaofeng Du, Xiaobo Qu, Yifan He, Di Guo
doaj   +1 more source

TI-CNN: Convolutional Neural Networks for Fake News Detection

CoRR, 2018
With the development of social networks, fake news for various commercial and political purposes has been appearing in large numbers and gotten widespread in the online world. With deceptive words, people can get infected by the fake news very easily and will share them without any fact-checking.
Yang Yang 0122, Lei Zheng 0001, Jiawei Zhang 0001, Qingcai Cui, Zhoujun Li 0001, Philip S. Yu   +5 more
openaire   +2 more sources

Learning‐Based Soft Robotic Grasping: Recent Progress and Remaining Challenges

Advanced Robotics Research, EarlyView.
This review analyzes learning‐based soft robotic grasping from a pipeline‐oriented perspective, encompassing soft gripper design, multimodal sensing, and learning‐based planning and control. It surveys key neural network architectures and benchmark datasets and identifies critical challenges such as sim‐to‐real transfer, generalization, and continual ...
Arnab Majumder, Jelizaveta Konstantinova, Graham Deacon, Kaspar Althoefer   +3 more
wiley   +1 more source

A Fourier Domain Training Framework for Convolutional Neural Networks Based on the Fourier Domain Pyramid Pooling Method and Fourier Domain Exponential Linear Unit

IEEE Access, 2019
convolutional neural networks (CNNs) in the frequency domain is of great significance for extending the deep learning principle to the frequency domain.
Jinhua Lin, Lin Ma, Yu Yao
doaj   +1 more source

Solid Harmonic Wavelet Bispectrum for Image Analysis

Advanced Science, EarlyView.
The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown, Mathilda Avirett‐Mackenzie, Carolin Villforth, Georgios Exarchakis   +3 more
wiley   +1 more source

Gender Classification Using a Convolutional Neural Network (CNN)

Abstract The purpose of this paper is to demonstrate an innovative convolutional neural network (also known as CNN) methodology for real-time categorization of gender via face photos. The suggested CNN architecture boasts much reduced computational complexity than the current methodologies used in pattern recognition applications.
Vyshnavi, Cherukuri, Homitha, Nookala Sai, Vasavi, Balabhadra, Bhavana, Mareedu, Bulla, Suneetha   +4 more
openaire   +2 more sources

HSI-CNN: A Novel Convolution Neural Network for Hyperspectral Image

CoRR, 2018
With the development of deep learning, the performance of hyperspectral image (HSI) classification has been greatly improved in recent years. The shortage of training samples has become a bottleneck for further improvement of performance. In this paper, we propose a novel convolutional neural network framework for the characteristics of hyperspectral ...
Yanan Luo, Jie Zou, Chengfei Yao, Tao Li, Gang Bai   +4 more
openaire   +2 more sources

Recent Advances in Laser‐Induced Graphene‐Based Gas Sensors: From Sensing Mechanisms to Biomedical Applications

Advanced Science, EarlyView.
Laser‐induced graphene (LIG) provides a scalable, laser‐direct‐written route to porous graphene architecture with tunable chemistry and defect density. Through heterojunction engineering, catalytic functionalization, and intrinsic self‐heating, LIG achieves highly sensitive and selective detection of NOX, NH3, H2, and humidity, supporting next ...
Md Abu Sayeed Biswas, Ankan Dutta, Shuvendu Das, Abu Musa Abdullah, Wanqing Zhang, Fatema Tuz Zohra, Huanyu Cheng   +6 more
wiley   +1 more source