Results 51 to 60 of about 4,047,749 (292)
A defect‐engineered Ag/Gd2O3:Nb2O5/Pt rare earth composite oxide memristor enables stable multilevel reservoir states through pulse driven conductance modulation. Experimentally measured device responses are incorporated into a device aware reservoir computing framework for CIFAR‐100 image classification, highlighting the potential of rare earth ...
Hammad Ghazanfar +9 more
wiley +1 more source
In recent years, convolutional neural networks (CNNs) have been introduced for pixel-wise hyperspectral image (HSI) classification tasks. However, some problems of the CNNs are still insufficiently addressed, such as the receptive field problem, small ...
Haimiao Ge +6 more
doaj +1 more source
Neuromorphic plasticity in OECTs is governed by the post‐stimulus evolution of coupled ionic and electronic states. Semiconductor chemistry and morphology, electrolyte composition and interfaces, and device architecture regulate ion injection, transport, confinement, and release, shifting responses from rapidly relaxing STP to metastable memory and ...
Inho Lee +9 more
wiley +1 more source
NeuroVisio SyncPatch integrates skin‐conformal electromyography (EMG) electrodes with camera‐tracked markers to jointly assess muscle activity and three‐dimensional knee kinematics during rehabilitation. Parallel feedback pathways provide real‐time kinematic guidance during movement and post‐trial neuromuscular feedback.
Bohyung Choi +11 more
wiley +1 more source
A New Deep Convolutional Network for Effective Hyperspectral Unmixing
Hyperspectral unmixing extracts pure spectral constituents (endmembers) and their corresponding abundance fractions from remotely sensed scenes. Most traditional hyperspectral unmixing methods require the results of other endmember extraction algorithms ...
Xuanwen Tao +7 more
doaj +1 more source
Ferroelectric Quantum Dots for Retinomorphic In‐Sensor Computing
This work has provided a protocol for fabricating retinomorphic phototransistors by integrating ferroelectric ligands with quantum dots. The resulting device combines ferroelectricity, optical responsiveness, and low‐power operation to enable adaptive signal amplification and high recognition accuracy under low‐light conditions, while supporting ...
Tingyu Long +26 more
wiley +1 more source
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj +8 more
wiley +1 more source
CNNs Avoid the Curse of Dimensionality by Learning on Patches
Despite the success of convolutional neural networks (CNNs) in numerous computer vision tasks and their extraordinary generalization performances, several attempts to predict the generalization errors of CNNs have only been limited to a posteriori ...
Vamshi C. Madala +2 more
doaj +1 more source
Accuracies of convolutional neural networks (CNNs) as compared against crowd consensus classifications of ‘snow’ or ‘no snow’ for three datasets.
Koen Hufkens (830074) +2 more
core +1 more source
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source

