Results 121 to 130 of about 33,048 (289)

Inhibitory Decay and Supercritical Brain Dynamics During Sleep Deprivation

Advanced Science, EarlyView.
Sleep deprivation progressively shifts human brain dynamics from near‐critical toward supercritical states, as revealed by neuronal avalanche analysis of resting‐state fMRI. These changes track subjective sleep pressure rather than vigilance lapses and show marked network heterogeneity. A circuit model suggests that reduced inhibitory efficacy provides
Dai Zhang, Liqin Zhou, Rong Wang, Yuehua Han, Zhentao Zuo, Yanghua Tian, Ke Zhou   +6 more
wiley   +1 more source

Binary-NeRV: Hybrid-Precision Weights Binarization for Efficient Neural Video Representation

IEEE Access
Neural implicit video representations such as NeRV have emerged as a powerful alternative to traditional video codecs. However, the high computational cost and full-precision storage of NeRV limit its practicality for resource-constrained and embedded ...
Tamer Shanableh
doaj   +1 more source

Neuromorphic Near‐Sensor and In‐Sensor Computing Enabled by Next‐Generation Material‐Based Sensors

Advanced Science, EarlyView.
This Review presents a structural framework that classifies neuromorphic sensing into near‐sensor and in‐sensor architectures, clarifying physical coupling between sensing and computation. The framework connects neural and synaptic device functions with recent advances in optical, mechanical, and chemical sensing, compares energy consumption and ...
Su Yeon Jung, Gwang Ya Kim, Sejin Kim, Hyunjong Seo, Se Gi Lee, Sang Min Won, Dongjoon Rhee, Joohoon Kang   +7 more
wiley   +1 more source

Experimental assessment of determining the average size of speckles

Вестник Самарского университета: Естественнонаучная серия
The paper proposes a method for estimating the average speckle size using experimentally recorded images of speckle fields on a CMOS matrix. This method can be useful when used in speckle interferometry methods when determining their metrological ...
Roman N. Sergeev
doaj   +1 more source

Fundamental Challenges, Physical Implementations, and Integration Strategies for Ising Machines in Large‐Scale Optimization Tasks

Advanced Electronic Materials, EarlyView.
Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley   +1 more source

In‐Sensor Computing by Soft Threshold Logic Gates Under Different Humidity Conditions

Advanced Electronic Materials, EarlyView.
Soft nanocomposite materials, based on gold cluster‐assembled thin films implanted in polydimethylsiloxane substrate, can perform reliable processing in ambient environmental conditions. Humidity influences the resistive switching and computational capabilities of the nanocomposites, that can be used as multifunctional material combining sensing ...
Giacomo Nadalini, Paolo Milani, Francesca Borghi   +2 more
wiley   +1 more source

Challenging the Limits of Binarization: A New Scheme Selection Policy Using Reinforcement Learning Techniques for Binary Combinatorial Problem Solving

Biomimetics
In this study, we introduce an innovative policy in the field of reinforcement learning, specifically designed as an action selection mechanism, and applied herein as a selector for binarization schemes.
Marcelo Becerra-Rozas, Broderick Crawford, Ricardo Soto, El-Ghazali Talbi, Jose M. Gómez-Pulido   +4 more
doaj   +1 more source

On the Role of Preprocessing and Memristor Dynamics in Reservoir Computing for Image Classification

Advanced Electronic Materials, EarlyView.
ABSTRACT Reservoir computing (RC) is an emerging recurrent neural network architecture that has attracted growing attention for its low training cost and modest hardware requirements. Memristor‐based circuits are particularly promising for RC, as their intrinsic dynamics can reduce network size and parameter overhead in tasks such as time‐series ...
Rishona Daniels, Duna Wattad, Ronny Ronen, David Saad, Shahar Kvatinsky   +4 more
wiley   +1 more source

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

Advanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour, Sara Soltanabadi Farshi, Tuanna Ozcan, Amir Mohammad Ketabchi, Alper Kiraz, Savas Tasoglu   +5 more
wiley   +1 more source

Research on persimmon fruit diameter accurate detection method based on improved RCNN instance segmentation algorithm

Frontiers in Plant Science
Aiming at the problem of inaccurate fruit recognition and fruit diameter detection in the persimmon inspection process, this research proposes a novel persimmon accurate recognition and fruit diameter detection algorithm based on the Region-based ...
Yuan Fang, Yuan Fang, Yangyang Liu, Yangyang Liu, Ya Feng, Ya Feng, Yougen Chen, Haikun Jiang   +7 more
doaj   +1 more source