Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving ...
Investigation of Deep Learning Techniques Used in Medicinal Plants Identification and Classification
Abstract: There is a global dependence on medicinal plants for the treatment of diverse health conditions, particularly in developing countries, where government medical facilities are inadequate.
A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic ...
Background Suicide rates have increased over the last couple of decades globally, particularly in the United States and among populations with lower economic status who present at safety-net ...
Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...
The electrocardiogram (ECG) is an important tool for exploring the structure and function of the heart due to its low cost, ease of use, efficiency, and non-invasive nature. With the rapid development ...
Abstract: The classification of cognitive load is crucial to evaluate mental effort in various tasks. Compared to physiological measures such as electroencephalography (EEG), electrocardiography (ECG) ...
Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Figure 1 illustrates the overall workflow of the hyperspectral ...
In large public multi-site fMRI datasets, the sample characteristics, data acquisition methods, and MRI scanner models vary across sites and datasets. This non-neural variability obscures neural ...
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