AIMC Topic: Neural Networks, Computer

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Emotion Recognition on Edge Devices: Training and Deployment.

Sensors (Basel, Switzerland)
Emotion recognition, among other natural language processing tasks, has greatly benefited from the use of large transformer models. Deploying these models on resource-constrained devices, however, is a major challenge due to their computational cost....

Earthquake-Induced Building-Damage Mapping Using Explainable AI (XAI).

Sensors (Basel, Switzerland)
Building-damage mapping using remote sensing images plays a critical role in providing quick and accurate information for the first responders after major earthquakes. In recent years, there has been an increasing interest in generating post-earthqua...

Cross Attention Squeeze Excitation Network (CASE-Net) for Whole Body Fetal MRI Segmentation.

Sensors (Basel, Switzerland)
Segmentation of the fetus from 2-dimensional (2D) magnetic resonance imaging (MRI) can aid radiologists with clinical decision making for disease diagnosis. Machine learning can facilitate this process of automatic segmentation, making diagnosis more...

Texture Image Classification Method of Porcelain Fragments Based on Convolutional Neural Network.

Computational intelligence and neuroscience
The texture image decomposition of porcelain fragments based on convolutional neural network is a functional algorithm based on energy minimization. It maps the image to a suitable space and can effectively decompose the image structure, texture, and...

Joint representation of color and form in convolutional neural networks: A stimulus-rich network perspective.

PloS one
To interact with real-world objects, any effective visual system must jointly code the unique features defining each object. Despite decades of neuroscience research, we still lack a firm grasp on how the primate brain binds visual features. Here we ...

Equivalent-input-disturbance estimator-based event-triggered control design for master-slave neural networks.

Neural networks : the official journal of the International Neural Network Society
This paper investigates the robust synchronization problem for a class of master-slave neural networks (MSNNs) subject to network-induced delays, unknown time-varying uncertainty, and exogenous disturbances. An equivalent-input-disturbance (EID) esti...

Assessing the utility of deep neural networks in predicting postoperative surgical complications: a retrospective study.

The Lancet. Digital health
BACKGROUND: Early detection of postoperative complications, including organ failure, is pivotal in the initiation of targeted treatment strategies aimed at attenuating organ damage. In an era of increasing health-care costs and limited financial reso...

Quantitative Analysis and Automated Lung Ultrasound Scoring for Evaluating COVID-19 Pneumonia With Neural Networks.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
As being radiation-free, portable, and capable of repetitive use, ultrasonography is playing an important role in diagnosing and evaluating the COVID-19 Pneumonia (PN) in this epidemic. By virtue of lung ultrasound scores (LUSS), lung ultrasound (LUS...

A Deep Learning Approach for Segmentation, Classification, and Visualization of 3-D High-Frequency Ultrasound Images of Mouse Embryos.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Segmentation and mutant classification of high-frequency ultrasound (HFU) mouse embryo brain ventricle (BV) and body images can provide valuable information for developmental biologists. However, manual segmentation and identification of BV and body ...

Possibility of Human Gender Recognition Using Raman Spectra of Teeth.

Molecules (Basel, Switzerland)
Gender determination of the human remains can be very challenging, especially in the case of incomplete ones. Herein, we report a proof-of-concept experiment where the possibility of gender recognition using Raman spectroscopy of teeth is investigate...