AIMC Topic: Deep Learning

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Extraction of Intangible Cultural Heritage Visual Elements by Deep Learning and Its Application in Grassland Tourism of the Silk Road Culture.

Computational intelligence and neuroscience
Inner Mongolia is rich in grassland tourism resources, and the development of grassland tourism is of great significance to Inner Mongolia tourism and promotion of grassland protection. To better promote the grassland tourism of the Silk Road culture...

Music Emotion Classification Method Based on Deep Learning and Improved Attention Mechanism.

Computational intelligence and neuroscience
Since the existing music emotion classification researches focus on the single-modal analysis of audio or lyrics, the correlation among models are neglected, which lead to partial information loss. Therefore, a music emotion classification method bas...

Study on the Application of Visual Communication Design in APP Interface Design in the Context of Deep Learning.

Computational intelligence and neuroscience
Visual communication concepts enable linguistics or semiotics to the teaching of visual communication designs, creating graphic designs into an innovative and scientific discipline. The use of storyline techniques in visual communication not only ins...

From YouTube to the brain: Transfer learning can improve brain-imaging predictions with deep learning.

Neural networks : the official journal of the International Neural Network Society
Deep learning has recently achieved best-in-class performance in several fields, including biomedical domains such as X-ray images. Yet, data scarcity poses a strict limit on training successful deep learning systems in many, if not most, biomedical ...

Deep Learning-Based Sensor Array: 3D Fluorescence Spectra of Gold Nanoclusters for Qualitative and Quantitative Analysis of Vitamin B Derivatives.

Analytical chemistry
Vitamin B derivatives (VB6Ds) are of great importance for all living organisms to complete their physiological processes. However, their excess in the body can cause serious problems. What is more, the qualitative and quantitative analysis of differe...

Deep-Learning-Based Wireless Visual Sensor System for Shiitake Mushroom Sorting.

Sensors (Basel, Switzerland)
The shiitake mushroom is the second-largest edible mushroom in the world, with a high nutritional and medicinal value. The surface texture of shiitake mushrooms can be quite different due to different growing environments, consequently leading to flu...

Deep Learning Staging of Liver Iron Content From Multiecho MR Images.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: MRI represents the most established liver iron content (LIC) evaluation approach by estimation of liver T2* value, but it is dependent on the choice of the measurement region and the software used for image analysis.

Development of a deep learning model for the histologic diagnosis of dysplasia in Barrett's esophagus.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: The risk of progression in Barrett's esophagus (BE) increases with development of dysplasia. There is a critical need to improve the diagnosis of BE dysplasia, given substantial interobserver disagreement among expert pathologist...

Deep-learning synthesized pseudo-CT for MR high-resolution pediatric cranial bone imaging (MR-HiPCB).

Magnetic resonance in medicine
PURPOSE: CT is routinely used to detect cranial abnormalities in pediatric patients with head trauma or craniosynostosis. This study aimed to develop a deep learning method to synthesize pseudo-CT (pCT) images for MR high-resolution pediatric cranial...

Deep learning-based quantitative susceptibility mapping (QSM) in the presence of fat using synthetically generated multi-echo phase training data.

Magnetic resonance in medicine
PURPOSE: To enable a fast and automatic deep learning-based QSM reconstruction of tissues with diverse chemical shifts, relevant to most regions outside the brain.