AIMC Topic: Feedback

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Hyperparameter Control Using Fuzzy Logic: Evolving Policies for Adaptive Fuzzy Particle Swarm Optimization Algorithm.

Evolutionary computation
Heuristic optimization methods such as particle swarm optimization (PSO) depend on their parameters to achieve optimal performance on a given class of problems. Some modifications of heuristic algorithms aim at adapting those parameters during the op...

STSF: Spiking Time Sparse Feedback Learning for Spiking Neural Networks.

IEEE transactions on neural networks and learning systems
Spiking neural networks (SNNs) are biologically plausible models known for their computational efficiency. A significant advantage of SNNs lies in the binary information transmission through spike trains, eliminating the need for multiplication opera...

The linguistic feedback of tourism robots significantly influences visitors' ecotourism behaviors.

Scientific reports
With the extensive application of artificial intelligence technology in the tourism industry, robot-assisted tourism has become a vital strategy for enhancing tourist experiences and promoting sustainable tourism practices. This study aims to explore...

[Neural network for auditory speech enhancement featuring feedback-driven attention and lateral inhibition].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
The processing mechanism of the human brain for speech information is a significant source of inspiration for the study of speech enhancement technology. Attention and lateral inhibition are key mechanisms in auditory information processing that can ...

Full Study, Model Verification, and Control of a Five Degrees of Freedom Hybrid Robotic-Assisted System for Neurosurgery.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Neurosurgery demands high precision, and robotic-assisted systems are increasingly employed to enhance surgical outcomes. This study focuses on a hybrid robotic-assisted system for neurosurgery, addressing forward and inverse kinematics, ...

The impact of AI feedback on the accuracy of diagnosis, decision switching and trust in radiography.

PloS one
Artificial intelligence decision support systems have been proposed to assist a struggling National Health Service (NHS) workforce in the United Kingdom. Its implementation in UK healthcare systems has been identified as a priority for deployment. Fe...

Dynamic Inverse Reinforcement Learning for Feedback-driven Reward Estimation in Brain Machine Interface Tasks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Reinforcement learning (RL)-based brain machine interfaces (BMIs) provide a promising solution for paralyzed people. Enhancing the decoding performance of RL-based BMIs relies on the design of effective reward signals. Inverse reinforcement learning ...

Assessment of Force Feedback Models in a Haptic Device Using Alignment Accuracy and Brain Activity.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
When controlling a robot's velocity, it is necessary to provide force feedback to the user, which shows the amount of input from the neutral position. In this paper, we introduce three distinct force feedback models, each with one or two parameters, ...

Modeling Precision Feedback Knowledge for Healthcare Professional Learning and Quality Improvement.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Healthcare providers learn continuously, but better support for provider learning is needed as new biomedical knowledge is produced at an increasing rate alongside widespread use of EHR data for clinical performance measurement. Precision feedback is...