Exploiting Ferroelectric and Spintronic Dynamics for Neural Network Computation
Advanced Intelligent Systems, EarlyView.Ferroelectric and spintronic devices, relying on the control of polarization and magnetization, offer intrinsically fast, durable, energy‐efficient, and low‐latency building blocks for analog in‐memory computing. The hysteretic dynamics of an order parameter are leveraged to provide nonvolatile, multistate memory and nonlinear switching. Brain‐inspired
Dashiell Harrison +4 more
wiley +1 more source
EdgeLane-SEG: an energy-efficient embedded edge AI framework for real-time road marking and lane lines detection with instance segmentation in ADAS and autonomous driving. [PDF]
Front Artif IntellChaman M +8 more
europepmc +1 more source
Interpretable Short‐Term Electric Load Forecasting
Advanced Intelligent Systems, EarlyView.A temporal fusion transformer is implemented to generate day‐ahead forecasts of the hourly electrical load of a departmentbuilding at an Italian university. A forecasting performance improvement of more than 25% compared with established benchmark models and a provision of inherent robust interpretability insights reveal the potential of this model for
Alessandro Nicola +6 more
wiley +1 more source
Real-time closed-loop feedback system for mouse mesoscale cortical signal and movement control. [PDF]
ElifeGupta PK, Murphy TH.
europepmc +1 more source
Equity valuation: NVIDIA Corporation
This report was developed to determine the fair value of NVIDIA’s shares on 29 January 2023 and to make a comparison between the obtained value and the actual close price observed at that date.
Gouveia, Francisco de Mesquita
core
A Language‐Guided Multimodal Foundation Model for Zero‐Shot and Multi‐Task Brain Signal Analysis
Advanced Intelligent Systems, EarlyView.METIS aligns brain signals with natural‐language instructions to enable zero‐shot and multi‐task brain signal analysis. Pretrained on over 70 000 h of EEG and iEEG recordings, it generalizes across sleep stage classification, epilepsy detection, and neurological disorder diagnosis, providing a scalable foundation model for clinically meaningful brain ...
Mingzhi Chen +3 more
wiley +1 more source
An Interpretable and Edge Deployable Spatio-Temporal Trajectory Prediction for Autonomous Driving. [PDF]
Sensors (Basel)Megalingam RK, Selvarajan NP, Vijay P.
europepmc +1 more source
Advanced Intelligent Systems, EarlyView.A hybrid Reinforcement Learning–Explainable AI framework integrates SHAP and LIME explanations directly into a Deep Q‐Network inference loop for real‐time ICU decision support. Trained on 18 142 mechanically ventilated stays from the eICU database, the system attains 93.0% decision accuracy, 20% fewer errors than RL alone, and a 91% clinician trust ...
Jannatul Ferdaus Disha +2 more
wiley +1 more source
The limits of bio-molecular modeling with large language models: a cross-scale evaluation. [PDF]
BioinformaticsXu Y, Zhou Y, Zhao T, Ma Z, An F, Ren Z.
europepmc +1 more source
Ecoefficiency Analysis and Regression in Data Conversion for Spiking Neural Network Training
Advanced Intelligent Systems, EarlyView.The environmental footprint of spiking neural networks is quantified during dataset encoding and training for autonomous driving regression across three benchmarks. Temporal depth emerges as the dominant driver of energy consumption and CO2 emissions, while the accuracy–energy trade‐off proves dataset‐dependent. On conventional hardware, spiking models
Fernando S. Martínez +3 more
wiley +1 more source