AIMC Topic: Neural Networks, Computer

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Bio-inspired multimodal learning with organic neuromorphic electronics for behavioral conditioning in robotics.

Nature communications
Biological systems interact directly with the environment and learn by receiving multimodal feedback via sensory stimuli that shape the formation of internal neuronal representations. Drawing inspiration from biological concepts such as exploration a...

Optimizing motor imagery BCI models with hard trials removal and model refinement.

Biomedical physics & engineering express
Deep learning models have demonstrated remarkable performance in the classification of motor imagery BCI systems. However, these models exhibit sensitivity to challenging trials, often called hard trials, leading to performance degradation. In this p...

Automated identification of toxigenic cyanobacterial genera for water quality control purposes.

Journal of environmental management
Cyanobacteria are the dominating microorganisms in aquatic environments, posing significant risks to public health due to toxin production in drinking water reservoirs. Traditional water quality assessments for abundance of the toxigenic genera in wa...

Contrastive Brain Network Learning via Hierarchical Signed Graph Pooling Model.

IEEE transactions on neural networks and learning systems
Recently, brain networks have been widely adopted to study brain dynamics, brain development, and brain diseases. Graph representation learning techniques on brain functional networks can facilitate the discovery of novel biomarkers for clinical phen...

Machine learning with taxonomic family delimitation aids in the classification of ephemeral beaked whale events in passive acoustic monitoring.

PloS one
Passive acoustic monitoring is an essential tool for studying beaked whale populations. This approach can monitor elusive and pelagic species, but the volume of data it generates has overwhelmed researchers' ability to quantify species occurrence for...

Federated learning inspired Antlion based orchestration for Edge computing environment.

PloS one
Edge computing is a scalable, modern, and distributed computing architecture that brings computational workloads closer to smart gateways or Edge devices. This computing model delivers IoT (Internet of Things) computations and processes the IoT reque...

A robust deep learning system for screening of obstructive sleep apnea using T-F spectrum of ECG signals.

Computer methods in biomechanics and biomedical engineering
Obstructive sleep apnea (OSA) is a non-communicable sleep-related medical condition marked by repeated disruptions in breathing during sleep. It may induce various cardiovascular and neurocognitive complications. Electrocardiography (ECG) is a useful...

SJFO: Sail Jelly Fish Optimization enabled VM migration with DRNN-based prediction for load balancing in cloud computing.

Network (Bristol, England)
The dynamic workload is evenly distributed among all nodes using balancing methods like hosts or VMs. Load Balancing as a Service (LBaaS) is another name for load balancing in the cloud. In this research work, the load is balanced by the application ...

Meta-learning based blind image super-resolution approach to different degradations.

Neural networks : the official journal of the International Neural Network Society
Although recent studies on blind single image super-resolution (SISR) have achieved significant success, most of them typically require supervised training on synthetic low resolution (LR)-high resolution (HR) paired images. This leads to re-training...

UGEE-Net: Uncertainty-guided and edge-enhanced network for image splicing localization.

Neural networks : the official journal of the International Neural Network Society
Image splicing, a prevalent method for image tampering, has significantly undermined image authenticity. Existing methods for Image Splicing Localization (ISL) struggle with challenges like limited accuracy and subpar performance when dealing with im...