AIMC Topic: Neural Networks, Computer

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LyricEmotionNet for robust emotion recognition with hybrid CapsNet-memory network architecture.

Scientific reports
With the rapid development of music streaming platforms, accurate understanding of lyric emotions has become crucial for enhancing personalized services in music recommendation systems. However, existing methods show significant limitations in proces...

Automating time frequency annotations of delphinid whistles by adapting a foundational transformer neural network.

Scientific reports
Automated detection of calls is essential to bioacoustic research where it is routine to collect large data sets that preclude effective human annotation. Automated analysis remains challenging due to variations in calls, varying noise backgrounds, a...

Interpretable deep multimodal-based tomato disease diagnosis and severity estimation.

Scientific reports
Plant diseases pose a significant threat to global food security, particularly in regions that rely heavily on crops that are vulnerable to disease, such as tomatoes. This research addresses the inefficiencies of traditional farming solutions by pres...

Multi head attention based deep learning framework for waxberry fruit object segmentation from high resolution remote sensing images.

Scientific reports
In some Asian countries, waxberries are special fruit that demand substantial labour for harvesting each season. To ease this burden, automated fruit-picking equipment has seen extensive development over the past decade. However, accurately segmentin...

Investigating the capability of deep learning models to predict age and biological sex from anterior segment ophthalmic imaging: a multi-centre retrospective study.

BMJ open
OBJECTIVE: To assess the capability of a convolutional neural network trained by transfer learning on anterior segment optical coherence tomography (AS-OCT) images, Placido-disk corneal topography images and external photographs to predict age and bi...

Identifying EEG-based neurobehavioral risk markers of gaming addiction using machine learning and iowa gambling task.

Biomedical physics & engineering express
Internet Gaming Disorder (IGD), Gaming Disorder (GD), and Internet Addiction represent behavioral patterns with significant psychological and neurological consequences. Affected individuals often disengage from routine activities and exhibit distress...

Self-learning model fusion for network anomaly detection: A hybrid CNN-LSTM-transformer framework.

PloS one
The rapid evolution of cyber threats poses significant challenges to the adaptability and performance of anomaly detection systems. This study presents an innovative hybrid deep learning framework that integrates Convolutional Neural Networks (CNN), ...

Neuro-computational surrogates for aqueous fractional-order nekton-plankton spatiotemporal dynamics under toxicant stress, refuge efficacy, and nutrient flux modulation.

Water research
In aquatic ecosystems, the triadic relationship among phytoplankton, zooplankton, and their piscine predators constitutes a delicately balanced ecological continuum where nutrient cycling, toxin transfer, and spatial refugia collectively dictate popu...

GADRC: a graph-based approach for drug repositioning with deep residual networks and computational feature-guided undersampling.

Journal of computer-aided molecular design
Drug repositioning (DR) is a highly promising research strategy aimed at discovering new therapeutic indications for existing drugs. Current computational DR methods have become effective tools for uncovering drug-disease associations, yet they suffe...

TDMAR-Net: a frequency-aware tri-domain diffusion network for CT metal artifact reduction.

Physics in medicine and biology
Metal implants and other high-density objects cause significant artifacts in computed tomography (CT) images, hindering clinical diagnosis. Traditional metal artifact reduction methods often leave residual artifacts due to sinogram edges discontinuit...