AIMC Topic: Deep Learning

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DNA-CBIR: DNA Translation Inspired Codon Pattern-Based Deep Image Feature Extraction for Content-Based Image Retrieval.

IEEE transactions on nanobioscience
DNA is emerging as a promising medium for storing huge volumes of data in a confined space that remains intact for thousands of years. Although this technique is very efficient, especially for multimedia data like images, there is a lack of efficient...

Anxiety disorder identification with biomarker detection through subspace-enhanced hypergraph neural network.

Neural networks : the official journal of the International Neural Network Society
In this study, we propose a subspace-enhanced hypergraph neural network (seHGNN) for classifying anxiety disorders (AD), which are prevalent mental illnesses that affect a significant portion of the global population. Our seHGNN model utilizes a lear...

Rapid detection of the viability of naturally aged maize seeds using multimodal data fusion and explainable deep learning techniques.

Food chemistry
Seed viability, a key indicator for quality assessment, directly impacts the emergence of field seedlings. The existing nondestructive testing model for maize seed vitality based on naturally aged seeds and predominantly relying on single-modal data ...

A general deep learning model for predicting and classifying pea protein content via visible and near-infrared spectroscopy.

Food chemistry
Rapid and accurate detection of pea protein content is crucial for breeding and ensuring food quality. This study introduces the PeaNet model, which employs an improved convolutional neural network architecture to predict and classify pea protein con...

Extracting True Virus SERS Spectra and Augmenting Data for Improved Virus Classification and Quantification.

ACS sensors
Surface-enhanced Raman spectroscopy (SERS) is a transformative tool for infectious disease diagnostics, offering rapid and sensitive species identification. However, background spectra in biological samples complicate analyte peak detection, increase...

[Advances in low-dose cone-beam computed tomography image reconstruction methods based on deep learning].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Cone-beam computed tomography (CBCT) is widely used in dentistry, surgery, radiotherapy and other medical fields. However, repeated CBCT scans expose patients to additional radiation doses, increasing the risk of secondary malignant tumors. Low-dose ...

Deep learning-based forecasting of daily maximum ozone levels and assessment of socioeconomic and health impacts in South Korea.

The Science of the total environment
Accurate forecasting of ground-level ozone (O) is essential for assessing its public health and socioeconomic impacts. This study evaluates the performance of three deep learning models-Deep Convolutional Neural Networks (Deep-CNN), Long Short-Term M...

Deep mechanism design: Learning social and economic policies for human benefit.

Proceedings of the National Academy of Sciences of the United States of America
Human society is coordinated by mechanisms that control how prices are agreed, taxes are set, and electoral votes are tallied. The design of robust and effective mechanisms for human benefit is a core problem in the social, economic, and political sc...