Results 201 to 210 of about 1,160,496 (247)
The Neural Network for Sign Language Comprehension. [PDF]
Terhune-Cotter B, Emmorey K.
europepmc +1 more source
A van der Waals optoelectronic synaptic device based on a ReS2/WSe2 heterostructure and oxygen‐treated h‐BN is presented, which enables both positive and negative PSCs through photocarrier polarity reversal. Bidirectional plasticity arises from gate‐tunable band bending and charge trapping‐induced quasi‐doping.
Hyejin Yoon +9 more
wiley +1 more source
ICU-EEG Pattern Detection by a Convolutional Neural Network. [PDF]
Degano G +5 more
europepmc +1 more source
Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics
Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha +18 more
wiley +1 more source
Neural network modeling of psychoanalytic concepts. [PDF]
Levine DS +2 more
europepmc +1 more source
Integrative Approaches for DNA Sequence‐Controlled Functional Materials
DNA is emerging as a programmable building block for functional materials with applications in biomimicry, biochemical, and mechanical information processing. The integration of simulations, experiments, and machine learning is explored as a means to bridge DNA sequences with macroscopic material properties, highlighting current advances and providing ...
Aaron Gadzekpo +4 more
wiley +1 more source
Impact of Neuron Models on Spiking Neural Network Performance: A Complexity-based Classification Approach. [PDF]
Rudnicka Z, Szczepanski J, Pregowska A.
europepmc +1 more source
Machine Learning Prediction of Airfoil Aerodynamic Performance Using Neural Network Ensembles [PDF]
Diana-Andreea Sterpu +4 more
openalex +1 more source
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee +17 more
wiley +1 more source

