AIMC Topic: Deep Learning

Clear Filters Showing 13371 to 13380 of 28423 articles

Evaluation Model of New Socialist Countryside Construction Based on a Multilayer Neural Network in a Complex Environment.

Journal of environmental and public health
The creation of a deep neural network model with numerous hidden layers enables the layer-by-layer extraction of features from the input high-dimensional data, enabling the identification of the data's low-dimensional nested structure and the develop...

A Multiview Deep Learning Method for Brain Functional Connectivity Classification.

Computational intelligence and neuroscience
The brain functional connectivity classification based on deep learning is a research hotspot nowadays. However, the classification performance is far behind the demand of clinical applications. To alleviate the problem, this paper proposes a multivi...

Deep Learning Coronary Artery Calcium Scores from SPECT/CT Attenuation Maps Improve Prediction of Major Adverse Cardiac Events.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Low-dose ungated CT attenuation correction (CTAC) scans are commonly obtained with SPECT/CT myocardial perfusion imaging. Despite the characteristically low image quality of CTAC, deep learning (DL) can potentially quantify coronary artery calcium (C...

Active deep learning from a noisy teacher for semi-supervised 3D image segmentation: Application to COVID-19 pneumonia infection in CT.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Supervised deep learning has become a standard approach to solving medical image segmentation tasks. However, serious difficulties in attaining pixel-level annotations for sufficiently large volumetric datasets in real-life applications have highligh...

Comparative performance assessment of deep learning based image steganography techniques.

Scientific reports
Increasing data infringement while transmission and storage have become an apprehension for the data owners. Even the digital images transmitted over the network or stored at servers are prone to unauthorized access. However, several image steganogra...

DLoopCaller: A deep learning approach for predicting genome-wide chromatin loops by integrating accessible chromatin landscapes.

PLoS computational biology
In recent years, major advances have been made in various chromosome conformation capture technologies to further satisfy the needs of researchers for high-quality, high-resolution contact interactions. Discriminating the loops from genome-wide conta...

Investigation on Deep Learning Model of College English Based on Multimodal Learning Method.

Computational intelligence and neuroscience
Deep learning refers to active learning that allows students to perceive, experience, understand, and apply knowledge. Deep learning focuses on the mastery of knowledge and skills and more on the cultivation of higher-order thinking skills such as aw...

A novel deep learning approach for sickle cell anemia detection in human RBCs using an improved wrapper-based feature selection technique in microscopic blood smear images.

Biomedizinische Technik. Biomedical engineering
Sickle Cell Anemia (SCA) is a disorder in Red Blood Cells (RBCs) of human blood. Children under five years and pregnant women are mostly affected by SCA. Early diagnosis of this ailment can save lives. In recent years, the computer aided diagnosis of...

Rationalized deep learning super-resolution microscopy for sustained live imaging of rapid subcellular processes.

Nature biotechnology
The goal when imaging bioprocesses with optical microscopy is to acquire the most spatiotemporal information with the least invasiveness. Deep neural networks have substantially improved optical microscopy, including image super-resolution and restor...