AIMC Topic: Deep Learning

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Chronological age estimation from human microbiomes with transformer-based Robust Principal Component Analysis.

Communications biology
Deep learning for microbiome analysis has shown potential for understanding microbial communities and human phenotypes. Here, we propose an approach, Transformer-based Robust Principal Component Analysis(TRPCA), which leverages the strengths of trans...

Contrastive representation learning with transformers for robust auditory EEG decoding.

Scientific reports
Decoding of continuous speech from electroencephalography (EEG) presents a promising avenue for understanding neural mechanisms of auditory processing and developing applications in hearing diagnostics. Recent advances in deep learning have improved ...

Predict the writer's trait emotional intelligence from reproduced calligraphy.

Scientific reports
Trait emotional intelligence (EI) describes an individual's ability to control their emotions. In Chinese calligraphy, there is a saying that "the character reflects the person." This raises a hypothesis: is it possible to predict a writer's trait EI...

Ensemble-based sesame disease detection and classification using deep convolutional neural networks (CNN).

Scientific reports
This study presents an ensemble-based approach for detecting and classifying sesame diseases using deep convolutional neural networks (CNNs). Sesame is a crucial oilseed crop that faces significant challenges from various diseases, including phyllody...

Predictive Modeling of Osteonecrosis of the Femoral Head Progression Using MobileNetV3_Large and Long Short-Term Memory Network: Novel Approach.

JMIR medical informatics
BACKGROUND: The assessment of osteonecrosis of the femoral head (ONFH) often presents challenges in accuracy and efficiency. Traditional methods rely on imaging studies and clinical judgment, prompting the need for advanced approaches. This study aim...

Improved early-stage crop classification using a novel fusion-based machine learning approach with Sentinel-2A and Landsat 8-9 data.

Environmental monitoring and assessment
Crop classification during the early stages is challenging because of the striking similarity in spectral and texture features among various crops. To improve classification accuracy, this study proposes a novel fusion-based deep learning approach. T...

Pyramidal attention-based T network for brain tumor classification: a comprehensive analysis of transfer learning approaches for clinically reliable and reliable AI hybrid approaches.

Scientific reports
Brain tumors are a significant challenge to human health as they impair the proper functioning of the brain and the general quality of life, thus requiring clinical intervention through early and accurate diagnosis. Although current state-of-the-art ...

An improved domain-adversarial network for predicting hemodialysis adequacy.

Biomedical physics & engineering express
Hemodialysis (HD) is the primary life-sustaining treatment for patients with end-stage renal disease (ESRD). However, current real-time monitoring methods during dialysis are costly, complex, and not widely adopted. Therefore, this study aims to prop...

Strategies to Decipher Neuron Identity from Extracellular Recordings in Behaving Nonhuman Primates.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Identification of the neuron type is critical when using extracellular recordings in awake, behaving animal subjects to understand computation in neural circuits. Yet, modern recording probes have limited power to resolve neuron identity. Here, we pr...

Mangrove species classification using a proposed ensemble U-Net model and Planet satellite imagery: A case study in Ngoc Hien district, Ca Mau province, Vietnam.

PloS one
Land cover and plant species identification using satellite images and deep learning approaches have recently been a widely addressed area of research. However, mangroves, a specific species that have significantly declined in quantity and quality wo...