AIMC Topic: Task Performance and Analysis

Clear Filters Showing 81 to 90 of 250 articles

Reward-predictive representations generalize across tasks in reinforcement learning.

PLoS computational biology
In computer science, reinforcement learning is a powerful framework with which artificial agents can learn to maximize their performance for any given Markov decision process (MDP). Advances over the last decade, in combination with deep neural netwo...

A Cyber-Physical-Human System for One-to-Many UAS Operations: Cognitive Load Analysis.

Sensors (Basel, Switzerland)
The continuing development of avionics for Unmanned Aircraft Systems (UASs) is introducing higher levels of intelligence and autonomy both in the flight vehicle and in the ground mission control, allowing new promising operational concepts to emerge....

Evaluation of mental workload during automobile driving using one-class support vector machine with eye movement data.

Applied ergonomics
The aim of this study is to investigate the usefulness of the anomaly detection method by one-class support vector machine (OCSVM) for the evaluation of mental workload (MWL) during automobile driving. Twelve students (six males and six females) part...

Automatic task recognition in a flexible endoscopy benchtop trainer with semi-supervised learning.

International journal of computer assisted radiology and surgery
PURPOSE: Inexpensive benchtop training systems offer significant advantages to meet the increasing demand of training surgeons and gastroenterologists in flexible endoscopy. Established scoring systems exist, based on task duration and mistake evalua...

Nonlinear ICA of fMRI reveals primitive temporal structures linked to rest, task, and behavioral traits.

NeuroImage
Accumulating evidence from whole brain functional magnetic resonance imaging (fMRI) suggests that the human brain at rest is functionally organized in a spatially and temporally constrained manner. However, because of their complexity, the fundamenta...

Measurement and identification of mental workload during simulated computer tasks with multimodal methods and machine learning.

Ergonomics
This study attempted to multimodally measure mental workload and validate indicators for estimating mental workload. A simulated computer work composed of mental arithmetic tasks with different levels of difficulty was designed and used in the experi...

Integrating autonomously navigating assistance systems into the clinic: guiding principles and the ANTS-OR approach.

International journal of computer assisted radiology and surgery
PURPOSE: Autonomously self-navigating clinical assistance systems (ASCAS) seem highly promising for improving clinical workflows. There is great potential for easing staff workload and improving overall efficiency by reducing monotonous and physicall...

DGaze: CNN-Based Gaze Prediction in Dynamic Scenes.

IEEE transactions on visualization and computer graphics
We conduct novel analyses of users' gaze behaviors in dynamic virtual scenes and, based on our analyses, we present a novel CNN-based model called DGaze for gaze prediction in HMD-based applications. We first collect 43 users' eye tracking data in 5 ...

Interpreting neural decoding models using grouped model reliance.

PLoS computational biology
Machine learning algorithms are becoming increasingly popular for decoding psychological constructs based on neural data. However, as a step towards bridging the gap between theory-driven cognitive neuroscience and data-driven decoding approaches, th...

DeepCQ: Deep multi-task conditional quantification network for estimation of left ventricle parameters.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Automatic cardiac left ventricle (LV) quantification plays an important role in assessing cardiac function. Although many advanced methods have been put forward to quantify related LV parameters, automatic cardiac LV quantif...