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Results 141 to 150 of about 86,091 (310)

A Study on Convergence of Competitive CNNs

, 2007
In a series of papers published in the seventies, Grossberg has developed a geometric approach for analyzing the global dynamical behavior and convergence properties of a class of competitive dynamical systems.
M. Di Marco +9 more
core +1 more source

Bias‐Tunable Two‐Terminal Organic Photodetector for Intelligent Imaging

Advanced Science, EarlyView.
A vertically stacked two‐terminal photodetector with a symmetric donor–acceptor–donor trilayer active exhibits reconfigurable photoresponse with bias‐tunable magnitude and polarity, together with sub‐millisecond response speed and a wide tunable output window.
Sangin Hahn, Sanghoon Park, Seunghyup Yoo +2 more
wiley +1 more source

Fast R-CNN

2015 IEEE International Conference on Computer Vision (ICCV), 2015
To appear in ICCV ...
openaire +2 more sources

De Novo Design of Membrane‐Targeting Antimicrobial Peptides Against Gram‐Negative Bacteria Using a Generative Artificial Intelligence Framework

Advanced Science, EarlyView.
Antimicrobial resistance caused by Gram‐negative bacteria remains difficult to overcome due to the protective outer membrane. To address this challenge, a multi‐condition constrained generative AI framework, GenMTAMP is proposed for de novo membrane‐targeting antimicrobial peptide design by integrating physicochemical and spatial structure descriptors.
Jingxiao Yu +5 more
wiley +1 more source

AI‐Physics‐Experiment Trinity for Integrated Protein Dynamics Modeling

Advanced Science, EarlyView.
This review unites experiments, physics‐based simulations, and AI as a synergistic triad for protein dynamics modeling. It highlights integrative strategies, resolves sampling and forcefield bottlenecks, and outlines challenges and future directions for accurate, interpretable conformational ensemble prediction.
Chen Shi +4 more
wiley +1 more source

PRG4CNN: A Probabilistic Model Checking-Driven Robustness Guarantee Framework for CNNs

Entropy
As an important kind of DNN (deep neural network), CNN (convolutional neural network) has made remarkable progress and been widely used in the vision and decision-making of autonomous robots.
Yang Liu, Aohui Fang
doaj +1 more source

Synergistic Integration of Artificial Merkel Disc and Meissner Corpuscle via Dermal Papillary Structures for Mechanically Filtered Multimodal Tactile Sensing

Advanced Science, EarlyView.
A multimodal tactile sensor module that mimics the spatial arrangement and function of Merkel discs and Meissner corpuscles within the human papillary structure operates in a self‐powered manner, responding to both dynamic and static stimuli, achieving tactile perception more similar to human skin.
Jaehyeong Kim +4 more
wiley +1 more source

Uncertainty‐Aware Deep Ensembles for Robust and Reliable Chemical Sensor Arrays

Advanced Science, EarlyView.
A reliability‐aware electronic nose is developed using photothermally anchored metal‐catalyst decorated metal oxide nanofiber sensor arrays combined with deep ensemble learning. Diverse catalytic nanofiber channels generate gas‐specific response patterns, enabling selective identification and quantification of sulfur‐containing gases.
Sungwoo Eo +5 more
wiley +1 more source

fdavenport/multiyear-sst-prediction-with-cnns: v1.0

<p>first release</p ...
fdavenport
core +1 more source

Spherical Transformer: Adapting Spherical Signal to CNNs

, 2022
Convolutional neural networks (CNNs) have been widely used in various vision tasks, e.g. image classification, semantic segmentation, etc. Unfortunately, standard 2D CNNs are not well suited for spherical signals such as panorama images or spherical ...
Cai, Shen, Liu, Yuqi, Wang, Yin, Du, Haikuan +3 more
core

fos: computer and information sciences
computer vision and pattern recognition cs.cv
deep learning

convolutional neural networks
cnn
classification

machine learning cs.lg
convolutional neural network
image classification