AIMC Topic: Neural Networks, Computer

Clear Filters Showing 10161 to 10170 of 31376 articles

HUTNet: An Efficient Convolutional Neural Network for Handwritten Uchen Tibetan Character Recognition.

Big data
Recognition of handwritten Uchen Tibetan characters input has been considered an efficient way of acquiring mass data in the digital era. However, it still faces considerable challenges due to seriously touching letters and various morphological feat...

Prediction and Big Data Impact Analysis of Telecom Churn by Backpropagation Neural Network Algorithm from the Perspective of Business Model.

Big data
This study aims to transform the existing telecom operators from traditional Internet operators to digital-driven services, and improve the overall competitiveness of telecom enterprises. Data mining is applied to telecom user classification to proce...

Deeper neural network models better reflect how humans cope with contrast variation in object recognition.

Neuroscience research
Visual inputs are far from ideal in everyday situations such as in the fog where the contrasts of input stimuli are low. However, human perception remains relatively robust to contrast variations. To provide insights about the underlying mechanisms o...

Using Transfer Learning of Convolutional Neural Network on Neck Radiographs to Identify Acute Epiglottitis.

Journal of digital imaging
Acute epiglottitis (AE) is a life-threatening condition and needs to be recognized timely. Diagnosis of AE with a lateral neck radiograph yields poor reliability and sensitivity. Convolutional neural networks (CNN) are powerful tools to assist the an...

Rapid high-fidelity mapping using single-shot overlapping-echo acquisition and deep learning reconstruction.

Magnetic resonance in medicine
PURPOSE: To develop and evaluate a single-shot quantitative MRI technique called GRE-MOLED (gradient-echo multiple overlapping-echo detachment) for rapid mapping.

MEDL-Net: A model-based neural network for MRI reconstruction with enhanced deep learned regularizers.

Magnetic resonance in medicine
PURPOSE: To improve the MRI reconstruction performance of model-based networks and to alleviate their large demand for GPU memory.

Handcrafted Histological Transformer (H2T): Unsupervised representation of whole slide images.

Medical image analysis
Diagnostic, prognostic and therapeutic decision-making of cancer in pathology clinics can now be carried out based on analysis of multi-gigapixel tissue images, also known as whole-slide images (WSIs). Recently, deep convolutional neural networks (CN...

Image Noise Removal in Ultrasound Breast Images Based on Hybrid Deep Learning Technique.

Sensors (Basel, Switzerland)
Rapid improvements in ultrasound imaging technology have made it much more useful for screening and diagnosing breast problems. Local-speckle-noise destruction in ultrasound breast images may impair image quality and impact observation and diagnosis....

Artificial Intelligence and Machine Learning Technology Driven Modern Drug Discovery and Development.

International journal of molecular sciences
The discovery and advances of medicines may be considered as the ultimate relevant translational science effort that adds to human invulnerability and happiness. But advancing a fresh medication is a quite convoluted, costly, and protracted operation...

Intra-person multi-task learning method for chronic-disease prediction.

Scientific reports
In the medical field, various clinical information has been accumulated to help clinicians provide personalized medicine and make better diagnoses. As chronic diseases share similar characteristics, it is possible to predict multiple chronic diseases...