Calibration‐Free Electromyography Motor Intent Decoding Using Large‐Scale Supervised Pretraining
Calibration‐free electromyography motor intent decoding is enabled through large‐scale supervised pretraining across heterogeneous datasets. A Spatially Aware Feature‐learning Transformer processes variable channel counts and electrode geometries, allowing transfer across users and recording setups. On a held‐out benchmark, fine‐tuned cross‐user models
Alexander E. Olsson +3 more
wiley +1 more source
Critical Assessment of a Structure-Based Pipeline for Targeting the Long Noncoding RNA MALAT1. [PDF]
Aguti R +4 more
europepmc +1 more source
Hardware‐Based On‐Chip Learning Using a Ferroelectric AND‐Type Array With Random Synaptic Weights
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
Comparing energy-integrating detector and photon-counting detector-based breast cone beam CTs for microcalcification detection via Monte Carlo simulation. [PDF]
Ollah Ezzati A +6 more
europepmc +1 more source
High‐Speed Altitude Regulation With Neuromorphic Camera and Lightweight Embedded Computation
Neuromorphic cameras deliver rapid, high‐dynamic‐range sensing but overwhelm embedded processors at high speeds. This work presents a lightweight, optimized Lucas–Kanade optical flow method with parallelization, gyroscopic derotation, and adaptive event slicing.
Simon L. Jeger +3 more
wiley +1 more source
Comparing energy consumption and accuracy in text classification inference. [PDF]
Zschache J, Hartwig T.
europepmc +1 more source
This study introduces a data‐driven framework that combines deep reinforcement learning with classical path planning to achieve adaptive microrobot navigation. By training a surrogate neural network to emulate microrobot dynamics, the approach improves learning efficiency, reduces training time, and enables robust real‐time obstacle avoidance in ...
Amar Salehi +3 more
wiley +1 more source
Accelerating mesh-based Monte Carlo simulations using contemporary graphics ray-tracing hardware. [PDF]
Yan S, Dwyer D, Kaeli DR, Fang Q.
europepmc +1 more source
This study proposes a deep learning approach to evaluate the fatigue crack behavior in metals under overload conditions. Using digital image correlation to capture the strain near crack tips, convolutional neural networks classify crack states as normal, overload, or recovery, and accurately predict fatigue parameters.
Seon Du Choi +5 more
wiley +1 more source
Fast barcode calling based on <i>k</i>-mer distances. [PDF]
Uphoff RC +3 more
europepmc +1 more source

