AIMC Topic: Deep Learning

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Pre-gating and contextual attention gate - A new fusion method for multi-modal data tasks.

Neural networks : the official journal of the International Neural Network Society
Multi-modal representation learning has received significant attention across diverse research domains due to its ability to model a scenario comprehensively. Learning the cross-modal interactions is essential to combining multi-modal data into a joi...

A novel optimization-assisted multi-scale and dilated adaptive hybrid deep learning network with feature fusion for event detection from social media.

Network (Bristol, England)
Social media networks become an active communication medium for connecting people and delivering new messages. Social media can perform as the primary channel, where the globalized events or instances can be explored. Earlier models are facing the pi...

Narrowing the semantic gaps in U-Net with learnable skip connections: The case of medical image segmentation.

Neural networks : the official journal of the International Neural Network Society
Current state-of-the-art medical image segmentation techniques predominantly employ the encoder-decoder architecture. Despite its widespread use, this U-shaped framework exhibits limitations in effectively capturing multi-scale features through simpl...

Using Machine Learning for Endoscopic Detection of Low-Grade Subglottic Stenosis: A Proof of Principle.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
The current study trains, tests, and evaluates a deep learning algorithm to detect subglottic stenosis (SGS) on endoscopy. A retrospective review of patients undergoing microlaryngoscopy-bronchoscopy was performed. A pretrained image classifier (Resn...

Accelerated cardiac magnetic resonance imaging using deep learning for volumetric assessment in children.

Pediatric radiology
BACKGROUND: Ventricular volumetry using a short-axis stack of two-dimensional (D) cine balanced steady-state free precession (bSSFP) sequences is crucial in any cardiac magnetic resonance imaging (MRI) examination. This task becomes particularly chal...

E-BDL: Enhanced Band-Dependent Learning Framework for Augmented Radar Sensing.

Sensors (Basel, Switzerland)
Radar sensors, leveraging the Doppler effect, enable the nonintrusive capture of kinetic and physiological motions while preserving privacy. Deep learning (DL) facilitates radar sensing for healthcare applications such as gait recognition and vital-s...

Evaluation of transfer ensemble learning-based convolutional neural network models for the identification of chronic gingivitis from oral photographs.

BMC oral health
BACKGROUND: To evaluate the performances of several advanced deep convolutional neural network models (AlexNet, VGG, GoogLeNet, ResNet) based on ensemble learning for recognizing chronic gingivitis from screening oral images.

In Silico drug repurposing pipeline using deep learning and structure based approaches in epilepsy.

Scientific reports
Due to considerable global prevalence and high recurrence rate, the pursuit of effective new medication for epilepsy treatment remains an urgent and significant challenge. Drug repurposing emerges as a cost-effective and efficient strategy to combat ...