Results 91 to 100 of about 25,600 (268)
Advanced Intelligent Discovery, EarlyView.scTIGER2.0 is a deep‐learning framework that infers gene regulatory networks from single‐cell RNA sequencing data. By integrating correlation, pseudotime ordering, deep learning and bootstrap‐based significance testing, it reduces false positives and reveals directional gene interactions.
Nishi Gupta +3 more
wiley +1 more source
Spike-based computation using classical recurrent neural networks
Neuromorphic Computing and EngineeringSpiking neural networks (SNNs) are a type of artificial neural networks in which communication between neurons is only made of events, also called spikes.
Florent De Geeter +2 more
doaj +1 more source
Solving Data Overlapping Problem Using A Class‐Separable Extreme Learning Machine Auto‐Encoder
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.The overlapping and imbalanced data in classification present key challenges. Class‐separable extreme learning machine auto‐encoding (CS‐ELM‐AE) is proposed, which is an enhancement of ELM‐AE that better handles overlapping data by clustering points from the same class together. Applying oversampling addresses imbalanced data.
Ekkarat Boonchieng, Wanchaloem Nadda
wiley +1 more source
Predicting Performance of Hall Effect Ion Source Using Machine Learning
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park +8 more
wiley +1 more source
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.The systematic design of memristor‐based neural network is provided by analog conductance state parameters to accurately emulate the software‐based high‐resolution weight at discrete device level. The requirement of discrete analog conductance of memristor device is measured as ≈50 states with nonlinearity value of ≈0.142 within the deviation range of ...
Jingon Jang, Yoonseok Song, Sungjun Park
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
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
Equilibrium Propagation for Dissipative Dynamics
Advanced Intelligent Systems, EarlyView.This work develops local learning rules for damped linear dynamical systems, including mechanical structures and resistor‐inductor‐capacitor (RLC) circuits, by leveraging an effective action formulation. It demonstrates how physical systems can autonomously compute gradients and learn temporal patterns, enabling applications such as sound ...
Marc Berneman, Daniel Hexner
wiley +1 more source