AIMC Topic: Algorithms

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Deep Learning-Emerged Grid Cells-Based Bio-Inspired Navigation in Robotics.

Sensors (Basel, Switzerland)
Grid cells in the brain's entorhinal cortex are essential for spatial navigation and have inspired advancements in robotic navigation systems. This paper first provides an overview of recent research on grid cell-based navigation in robotics, focusin...

Skeleton Reconstruction Using Generative Adversarial Networks for Human Activity Recognition Under Occlusion.

Sensors (Basel, Switzerland)
Recognizing human activities from motion data is a complex task in computer vision, involving the recognition of human behaviors from sequences of 3D motion data. These activities encompass successive body part movements, interactions with objects, o...

Novelty Recognition: Fish Species Classification via Open-Set Recognition.

Sensors (Basel, Switzerland)
To support the sustainable use of marine resources, regulations have been proposed to reduce fish discards focusing on the registration of all listed species. To comply with such regulations, computer vision methods have been developed. Nevertheless,...

AI-Driven Framework for Enhanced and Automated Behavioral Analysis in Morris Water Maze Studies.

Sensors (Basel, Switzerland)
The Morris Water Maze (MWM) is a widely used behavioral test to assess the spatial learning and memory of animals, particularly valuable in studying neurodegenerative disorders such as Alzheimer's disease. Traditional methods for analyzing MWM experi...

Classifying metro drivers' cognitive distractions during manual operations using machine learning and random forest-recursive feature elimination.

Scientific reports
Metro drivers are more likely to trigger accidents if they suffer from cognitive distractions during manual driving. However, identifying metro drivers' cognitive distractions faces challenges as generally no obvious behavior can be found during the ...

Evolution of AI enabled healthcare systems using textual data with a pretrained BERT deep learning model.

Scientific reports
In the rapidly evolving field of healthcare, Artificial Intelligence (AI) is increasingly driving the promotion of the transformation of traditional healthcare and improving medical diagnostic decisions. The overall goal is to uncover emerging trends...

Deep learning-assisted identification and localization of ductal carcinoma from bulk tissue in-silico models generated through polarized Monte Carlo simulations.

Biomedical physics & engineering express
Despite significant progress in diagnosis and treatment, breast cancer remains a formidable health challenge, emphasizing the continuous need for research. This simulation study uses polarized Monte Carlo approach to identify and locate breast cancer...

AI-Generated Synthetic STIR of the Lumbar Spine from T1 and T2 MRI Sequences Trained with Open-Source Algorithms.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Lumbar spine MRIs can be time consuming, stressful for patients, and costly to acquire. In this work, we train and evaluate open-source generative adversarial network (GAN) to create synthetic lumbar spine MRI STIR volumes fro...

Deep Learning-Based ASPECTS Algorithm Enhances Reader Performance and Reduces Interpretation Time.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: ASPECTS is a long-standing and well-documented selection criterion for acute ischemic stroke treatment; however, the interpretation of ASPECTS is a challenging and time-consuming task for physicians with notable interobserver ...

Remote sensing of alcohol consumption using machine learning speckle pattern analysis.

Journal of biomedical optics
SIGNIFICANCE: Alcohol consumption monitoring is essential for forensic and healthcare applications. While breath and blood alcohol concentration sensors are currently the most common methods, there is a growing need for faster, non-invasive, and more...