AIMC Topic: Neural Networks, Computer

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LEyes: A lightweight framework for deep learning-based eye tracking using synthetic eye images.

Behavior research methods
Deep learning methods have significantly advanced the field of gaze estimation, yet the development of these algorithms is often hindered by a lack of appropriate publicly accessible training datasets. Moreover, models trained on the few available da...

Human activity recognition algorithms for manual material handling activities.

Scientific reports
Human Activity Recognition (HAR) using wearable sensors has prompted substantial interest in recent years due to the availability and low cost of Inertial Measurement Units (IMUs). HAR using IMUs can aid both the ergonomic evaluation of the performed...

Parallel convolutional neural networks for non-invasive cardiac hemodynamic estimation: integrating uncalibrated PPG signals with nonlinear feature analysis.

Physiological measurement
Understanding cardiac hemodynamic status (CHS) is essential for accurate cardiovascular health assessment, as it is governed by key parameters such as cardiac output (CO), systemic vascular resistance (SVR), and arterial compliance (AC). This study a...

Analysis of Deep Learning Techniques for Vehicle Detection and Reidentification Using Data from Multiple Drones and Public Datasets.

Anais da Academia Brasileira de Ciencias
The detection and re-identification of vehicles in dynamic environments, such as highways monitored by a swarm of drones, presents significant challenges, particularly due to the variability of images captured from different angles and under various ...

Advances in AI-based strategies and tools to facilitate natural product and drug development.

Critical reviews in biotechnology
Natural products and their derivatives have been important for treating diseases in humans, animals, and plants. However, discovering new structures from natural sources is still challenging. In recent years, artificial intelligence (AI) has greatly ...

Automated mitochondrial oxygen consumption (mitoVO) analysis via a bi-directional long short-term memory neural network.

Journal of clinical monitoring and computing
Monitoring in vivo mitochondrial oxygen tension (mitoPO) enables the measurement of mitochondrial oxygen consumption (mitoVO), providing deeper insights into the skin's mitochondrial environment. However, current mitoVO analysis often relies on manua...

Predicting protein-protein interaction with interpretable bilinear attention network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Protein-protein interactions (PPIs) play the key roles in myriad biological processes, helping to understand the protein function and disease pathology. Identification of PPIs and their interaction types through wet experime...

Influence pathways of noise exposure on people's negative emotions and health across different activity contexts: A neural network-based double machine learning approach.

Health & place
Noise is a major global environmental issue that raises concerns about both mental and physical health. However, few studies have investigated the mediating role of emotions in the pathways linking noise exposure to health outcomes. Additionally, man...

Multimodal contrastive learning for enhanced explainability in pediatric brain tumor molecular diagnosis.

Scientific reports
Despite the promising performance of convolutional neural networks (CNNs) in brain tumor diagnosis from magnetic resonance imaging (MRI), their integration into the clinical workflow has been limited. That is mainly due to the fact that the features ...

MuSIA: Exploiting multi-source information fusion with abnormal activations for out-of-distribution detection.

Neural networks : the official journal of the International Neural Network Society
In the open world, out-of-distribution (OOD) detection is crucial to ensure the reliability and robustness of deep learning models. Traditional OOD detection methods are often limited to using single-source information coupled with the abnormal activ...