AI Medical Compendium Topic

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Flexible Optical Synapses Based on InSe/MoS Heterojunctions for Artificial Vision Systems in the Near-Infrared Range.

ACS applied materials & interfaces
Near-infrared (NIR) synaptic devices integrate NIR optical sensitivity and synaptic plasticity, emulating the basic biomimetic function of the human visual system and showing great potential in NIR artificial vision systems. However, the lack of semi...

Incidental auditory category learning and visuomotor sequence learning do not compete for cognitive resources.

Attention, perception & psychophysics
The environment provides multiple regularities that might be useful in guiding behavior if one was able to learn their structure. Understanding statistical learning across simultaneous regularities is important, but poorly understood. We investigate ...

Adaptive Interaction Control of Compliant Robots Using Impedance Learning.

Sensors (Basel, Switzerland)
This paper presents an impedance learning-based adaptive control strategy for series elastic actuator (SEA)-driven compliant robots without the measurement of the robot-environment interaction force. The adaptive controller is designed based on the c...

Factorizing time-heterogeneous Markov transition for temporal recommendation.

Neural networks : the official journal of the International Neural Network Society
Temporal recommendation which recommends items to users with consideration of time information has been of wide interest in recent years. But huge event space, highly sparse user activities and time-heterogeneous dependency of temporal behaviors make...

Radiation therapist perceptions on how artificial intelligence may affect their role and practice.

Journal of medical radiation sciences
INTRODUCTION: The use of artificial intelligence (AI) has increased in medical radiation science, with advanced computing and modelling. Considering radiation therapists (RTs) perceptions of how this may affect their role is imperative, as this will ...

GC-MLP: Graph Convolution MLP for Point Cloud Analysis.

Sensors (Basel, Switzerland)
With the objective of addressing the problem of the fixed convolutional kernel of a standard convolution neural network and the isotropy of features making 3D point cloud data ineffective in feature learning, this paper proposes a point cloud process...

N-Omniglot, a large-scale neuromorphic dataset for spatio-temporal sparse few-shot learning.

Scientific data
Few-shot learning (learning with a few samples) is one of the most important cognitive abilities of the human brain. However, the current artificial intelligence systems meet difficulties in achieving this ability. Similar challenges also exist for b...

A Computational Complexity Perspective on Segmentation as a Cognitive Subcomputation.

Topics in cognitive science
Computational feasibility is a widespread concern that guides the framing and modeling of natural and artificial intelligence. The specification of cognitive system capacities is often shaped by unexamined intuitive assumptions about the search space...

IBLF-Based Adaptive Neural Control of State-Constrained Uncertain Stochastic Nonlinear Systems.

IEEE transactions on neural networks and learning systems
In this article, the adaptive neural backstepping control approaches are designed for uncertain stochastic nonlinear systems with full-state constraints. According to the symmetry of constraint boundary, two cases of controlled systems subject to sym...

End-to-End Hierarchical Reinforcement Learning With Integrated Subgoal Discovery.

IEEE transactions on neural networks and learning systems
Hierarchical reinforcement learning (HRL) is a promising approach to perform long-horizon goal-reaching tasks by decomposing the goals into subgoals. In a holistic HRL paradigm, an agent must autonomously discover such subgoals and also learn a hiera...