Results 181 to 190 of about 383,443 (287)
Advanced Intelligent Discovery, EarlyView.This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath +4 more
wiley +1 more source
Hardware‐Based On‐Chip Learning Using a Ferroelectric AND‐Type Array With Random Synaptic Weights
Advanced Intelligent Systems, EarlyView.This work demonstrates an energy‐efficient on‐chip learning system using an Metal‐Ferroelectric‐Insulator‐Semiconductor FeAND synaptic array. By employing a feedback alignment scheme with a separate backward array using fixed random weights, the system overcomes directional limitations of AND‐type arrays and achieves robust, low‐power learning suitable
Minsuk Song +8 more
wiley +1 more source
Device‐Level Implementation of Reservoir Computing With Memristors
Advanced Intelligent Systems, EarlyView.Reservoir computing (RC) is an emerging computing scheme that employs a reservoir and a single readout layer, which can be actualized in the nanoscale with memristors. As a comprehensive overview, the principles of RC and the switching mechanisms of memristors are discussed, followed by actual demonstrations of memristor‐based RC and the remaining ...
Sunbeom Park, Hyojung Kim, Ho Won Jang
wiley +1 more source
Advanced Intelligent Systems, EarlyView.Droplet‐based microfluidics enables precise, high‐throughput microscale reactions but continues to face challenges in scalability, reproducibility, and data complexity. This review examines how artificial intelligence enhances droplet generation, detection, sorting, and adaptive control and discusses emerging opportunities for clinical and industrial ...
Junyan Lai +10 more
wiley +1 more source
KDLM: Lightweight Brain Tumor Segmentation via Knowledge Distillation
Advanced Intelligent Systems, EarlyView.A lightweight student network is designed, which is based on multiscale and multilevel feature fusion and combined with the residual channel attention mechanism to achieve efficient feature extraction and fusion with very few parameters. A dual‐teacher collaborative knowledge distillation framework is proposed.
Baotian Li +4 more
wiley +1 more source
Neighbourhood characteristics and mental disorders in three Chinese cities: multilevel models from the World Mental Health Surveys. [PDF]
BMJ Open, 2017 Chiavegatto Filho ADP +10 more
europepmc +1 more source
A Flexible and Energy‐Efficient Compute‐in‐Memory Accelerator for Kolmogorov–Arnold Networks
Advanced Intelligent Systems, EarlyView.This article presents KA‐CIM, a compute‐in‐memory accelerator for Kolmogorov–Arnold Networks (KANs). It enables flexible and efficient computation of arbitrary nonlinear functions through cross‐layer co‐optimization from algorithm to device. KA‐CIM surpasses CPU, ASIC, VMM‐CIM, and prior KAN accelerators by 1–3 orders of magnitude in energy‐delay ...
Chirag Sudarshan +6 more
wiley +1 more source
Advanced Intelligent Systems, EarlyView.Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal +6 more
wiley +1 more source
Policy Implications of Achievement Testing Using Multilevel Models: The Case of Brazilian Elementary Schools. [PDF]
Front Psychol, 2016 Menezes IG +6 more
europepmc +1 more source
Methods for Setting Device Specifications for Analog In‐Memory Computing Inference
Advanced Intelligent Systems, EarlyView.Non‐volatile memories (NVMs) are being developed for analog in‐memory computing for energy‐efficient, high‐speed deep learning inference. As technology is moving to industry adoption, a method to define required NVM specifications is critical for improving performance and reducing manufacturing cost.
Zhenyu Wu +3 more
wiley +1 more source