Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Apr 23, 2020
Recently, deep learning has presented as a powerful approach to overcome the deficiencies of the conventional biochemical approaches. In this study, a method for discriminating medicinal plant Tetrastigma hemsleyanum from different origins was propos...
The interaction between humans and an NAO robot using deep convolutional neural networks (CNN) is presented in this paper based on an innovative end-to-end pipeline method that applies two optimized CNNs, one for face recognition (FR) and another one...
BACKGROUND: Protein succinylation has recently emerged as an important and common post-translation modification (PTM) that occurs on lysine residues. Succinylation is notable both in its size (e.g., at 100 Da, it is one of the larger chemical PTMs) a...
A massive number of biological entities, such as genes and mutations, are mentioned in the biomedical literature. The capturing of the semantic relatedness of biological entities is vital to many biological applications, such as protein-protein inter...
Deep learning methods are being increasingly widely used in static malware detection field because they can summarize the feature of malware and its variants that have never appeared before. But similar to the picture recognition model, the static ma...
BACKGROUND AND AIMS: Deep learning is an innovative algorithm based on neural networks. Wireless capsule endoscopy (WCE) is considered the criterion standard for detecting small-bowel diseases. Manual examination of WCE is time-consuming and can bene...
We present a Deep Learning framework for the prediction of chronological age from structural magnetic resonance imaging scans. Previous findings associate increased brain age with neurodegenerative diseases and higher mortality rates. However, the im...
Across the cell cycle, the subcellular organization undergoes major spatiotemporal changes that could in principle contain biological features that could potentially represent cell cycle phase. We applied convolutional neural network-based classifier...
Gliomas are the most common malignant brain tumors with different grades that highly determine the rate of survival in patients. Tumor segmentation and grading using magnetic resonance imaging (MRI) are common and essential for diagnosis and treatmen...
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