AIMC Topic: Deep Learning

Clear Filters Showing 14241 to 14250 of 28423 articles

Research and Implementation of Robot Vision Scanning Tracking Algorithm Based on Deep Learning.

Scanning
In order to solve the difficult problem of deep learning-based robot vision tracking algorithm research and implementation, a deep learning-based target tracking algorithm and a classical tracking algorithm were proposed. It mainly uses the combinati...

Estimating heading from optic flow: Comparing deep learning network and human performance.

Neural networks : the official journal of the International Neural Network Society
Convolutional neural networks (CNNs) have made significant advances over the past decade with visual recognition, matching or exceeding human performance on certain tasks. Visual recognition is subserved by the ventral stream of the visual system, wh...

Neurochemical Concentration Prediction Using Deep Learning vs Principal Component Regression in Fast Scan Cyclic Voltammetry: A Comparison Study.

ACS chemical neuroscience
Neurotransmitters, such as dopamine and serotonin, are responsible for mediating a wide array of neurologic functions, from memory to motivation. From measurements using fast scan cyclic voltammetry (FSCV), one of the main tools used to detect synapt...

bHLHDB: A next generation database of basic helix loop helix transcription factors based on deep learning model.

Journal of bioinformatics and computational biology
The basic helix loop helix (bHLH) superfamily is a large and diverse protein family that plays a role in various vital functions in nearly all animals and plants. The bHLH proteins form one of the largest families of transcription factors found in pl...

Sex differences in rTMS treatment response: A deep learning-based EEG investigation.

Brain and behavior
INTRODUCTION: The present study aimed to investigate sex differences in response to repetitive transcranial magnetic stimulation (rTMS) in Major Depressive Disorder (MDD) patients. Identifying the factors that mediate treatment response to rTMS in MD...

Self-supervised deep learning encodes high-resolution features of protein subcellular localization.

Nature methods
Explaining the diversity and complexity of protein localization is essential to fully understand cellular architecture. Here we present cytoself, a deep-learning approach for fully self-supervised protein localization profiling and clustering. Cytose...

Clinical Validation of a Deep-Learning Segmentation Software in Head and Neck: An Early Analysis in a Developing Radiation Oncology Center.

International journal of environmental research and public health
BACKGROUND: Organs at risk (OARs) delineation is a crucial step of radiotherapy (RT) treatment planning workflow. Time-consuming and inter-observer variability are main issues in manual OAR delineation, mainly in the head and neck (H & N) district. D...

A review of deep learning applications in human genomics using next-generation sequencing data.

Human genomics
Genomics is advancing towards data-driven science. Through the advent of high-throughput data generating technologies in human genomics, we are overwhelmed with the heap of genomic data. To extract knowledge and pattern out of this genomic data, arti...

A process mining- deep learning approach to predict survival in a cohort of hospitalized COVID-19 patients.

BMC medical informatics and decision making
BACKGROUND: Various machine learning and artificial intelligence methods have been used to predict outcomes of hospitalized COVID-19 patients. However, process mining has not yet been used for COVID-19 prediction. We developed a process mining/deep l...

Deep learning as a novel method for endoscopic diagnosis of chronic atrophic gastritis: a prospective nested case-control study.

BMC gastroenterology
BACKGROUND AND AIMS: Chronic atrophic gastritis (CAG) is a precancerous disease that often leads to the development of gastric cancer (GC) and is positively correlated with GC morbidity. However, the sensitivity of the endoscopic diagnosis of CAG is ...