Convolutional neural networks cnns

Results 241 to 250 of about 73,468 (309)

Exploiting Ferroelectric and Spintronic Dynamics for Neural Network Computation

Advanced Intelligent Systems, EarlyView.
Ferroelectric and spintronic devices, relying on the control of polarization and magnetization, offer intrinsically fast, durable, energy‐efficient, and low‐latency building blocks for analog in‐memory computing. The hysteretic dynamics of an order parameter are leveraged to provide nonvolatile, multistate memory and nonlinear switching. Brain‐inspired
Dashiell Harrison +4 more
wiley +1 more source

A Review and Experimental Analysis of Supervised Learning Systems and Methods for Protein-Protein Interaction Detection. [PDF]

Int J Mol Sci
Taha K.
europepmc +1 more source

Soft Active Electromyography Interface for Machine Learning‐Enabled Silent Speech Recognition

Advanced Intelligent Systems, EarlyView.
A soft, hand‐worn electromyography interface enables intent‐driven silent speech recognition without continuous facial attachment. The device integrates liquid‐metal interconnects, a transparent flexible circuit, and elastomer encapsulation with a fingertip electrode that contacts perioral muscles only on demand.
Yuta Kurotaki +8 more
wiley +1 more source

Automated Melanocytic Lesion Classification: Capsule Networks Trained With Synthetic Images Can Outperform Networks Trained With Real Images. [PDF]

Australas J Dermatol
Chai H, Gilmore S.
europepmc +1 more source

Enhanced Monocular Depth Estimation Using ResNet Backbone and Multiscale Feature Decoding for Precise Object Distance Measurement

Advanced Intelligent Systems, EarlyView.
A lightweight monocular perception framework generates high‐fidelity depth maps and integrates YOLOv8 detection to estimate object‐wise distances from a single RGB image. Evaluated on KITTI and the proposed D‐Far250 dataset, the system demonstrates accurate long‐range perception up to 250 m while maintaining real‐time performance, enabling scalable ...
Faseeh Muhammad +5 more
wiley +1 more source

Hybrid deep learning model for brain age prediction using time-distributed convolutional and bidirectional LSTM networks. [PDF]

Sci Rep
Mahmoud E, Elshennawy NM, Elkholy A.
europepmc +1 more source

Scene‐Customized Learning for Multi‐Depth 3D Phase‐Only Hologram Generation

Advanced Intelligent Systems, EarlyView.
Scene‐customized geometric modeling constructs GM‐4K, a controllable 4K RGB‐D dataset for learning‐based multi‐depth hologram generation. By tuning intensity spectra and depth‐region sampling, the dataset reveals how training‐data statistics affect phase‐only hologram encoding and supports a spectral test framework for evaluating model generalization ...
Yanan Zhang +5 more
wiley +1 more source

Is the molecular microenvironment of the latent HIV reservoir predictable using deep learning approaches? [PDF]

J Virol
Chen H-C.
europepmc +1 more source

Overcoming the Phase Discontinuity Problem in RIS Optimization: A Robust and Scalable Phase‐Aware Deep Regression Framework via Hybrid CNN–LSTM Architecture

Advanced Intelligent Systems, EarlyView.
The phase discontinuity problem—where the cyclic nature of phase angles causes catastrophic errors near the ±π boundary—is a fundamental obstacle in learning‐based reconfigurable intelligent surface (RIS) optimization. A phase‐aware hybrid CNN–LSTM framework resolves this by decomposing phase predictions into sine–cosine components, mapping circular ...
Seda Savaşçı Şen +3 more
wiley +1 more source

Foveated Retinotopy Improves Classification and Localization in Convolutional Neural Networks. [PDF]

Vision (Basel)
Jérémie JN, Daucé E, Perrinet LU.
europepmc +1 more source

convolutional neural networks
deep learning
convolutional neural network

physics
cnn
convolutional neural network cnn

computer vision