Results 71 to 80 of about 53,606 (313)
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
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 +4 more
openaire +2 more sources
Recent Advances in Decoupling Strategies for Soft Sensors
Advanced Science, EarlyView.This review provides an overview of recent advances in decoupling strategies for soft sensors. It summarizes single‐modal sensors that are insensitive to stretching, bending, crosstalk, and other environmental interferences, and highlights emerging multimodal decoupling methods enabled by spatiotemporal information and machine learning.
Yangbo Yuan +4 more
wiley +1 more source
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
De Novo Multi‐Mechanism Antimicrobial Peptide Design via Multimodal Deep Learning
Advanced Science, EarlyView.Current AI‐driven peptide discovery often overlooks complex structural data. This study presents M3‐CAD, a generative pipeline that leverages 3D voxel coloring and a massive database of over 12 000 peptides to capture nuanced physicochemical contexts.
Xiaojuan Li +23 more
wiley +1 more source
Tunable Switching Mechanisms in HfZrO2‐Based Tunnel Junctions for High‐Performance Synaptic Arrays
Advanced Science, EarlyView.This work demonstrates hybrid switching in engineered HZO‐based FTJs, enabled by controlled interlayer design and oxygen scavenging dynamics. The combined switching mechanism produces robust multilevel conductance states in large crossbar arrays, offering a materials‐driven pathway toward scalable in‐memory computing with enhanced tunability and ...
Jiwon You +8 more
wiley +1 more source
Unveil Fundamental Graph Properties for Neural Architecture Search
Advanced Science, EarlyView.This paper proposes NASGraph, a graph‐based framework that represents neural architectures as graphs whose structural properties determine performance. By revealing structure–performance relationships, NASGraph enables efficient neural architecture search with significantly reduced computation.
Zhenhan Huang +4 more
wiley +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 +3 more
wiley +1 more source
NanoLoop: A Deep Learning Framework Leveraging Nanopore Sequencing for Chromatin Loop Prediction
Advanced Science, EarlyView.Chromatin loops are central to gene regulation and 3D genome organization. Leveraging Nanopore sequencing's ability to jointly capture DNA sequence and methylation, we present NanoLoop, the first framework for genome‐wide chromatin loop prediction using Nanopore data.
Wenjie Huang +5 more
wiley +1 more source