Work Force

Neural network training method for materials science based on multi-source databases.

The fourth paradigm of science has achieved great success in material discovery and it highlights th...

GeneralizedDTA: combining pre-training and multi-task learning to predict drug-target binding affinity for unknown drug discovery.

BACKGROUND: Accurately predicting drug-target binding affinity (DTA) in silico plays an important ro...

Tuberculosis Detection from Chest Radiographs: Stop Training Radiologists Now.

Artificial intelligence system for training diagnosis and differentiation with molar incisor hypomineralization (MIH) and similar pathologies.

OBJECTIVES: Molar incisor hypomineralization (MIH) is a difficult-to-diagnose developmental disorder...

Low precision decentralized distributed training over IID and non-IID data.

Decentralized distributed learning is the key to enabling large-scale machine learning (training) on...

Digital Stereotypes in HMI-The Influence of Feature Quantity Distribution in Deep Learning Models Training.

This paper proposes a concept of Digital Stereotypes, observed during research on quantitative overr...

Robot-assisted training with functional electrical stimulation enhances lower extremity function after spinal cord injury.

INTRODUCTION: Functional electrical stimulation (FES) synchronized with robot-assisted lower extremi...

Is Leg-Driven Treadmill-Based Exoskeleton Robot Training Beneficial to Poststroke Patients: A Systematic Review and Meta-analysis.

OBJECTIVE: The aim of the study is to systematically review the effects of leg-driven treadmill-base...

Training in the protocol for robotic undocking for life emergency support (RULES) improves team communication, coordination and reduces the time required to decouple the robotic system from the patient.

INTRODUCTION: Robotic surgery has expanded on it's surgical application and it is also noted an incr...

Shape-Texture Debiased Training for Robust Template Matching.

Finding a template in a search image is an important task underlying many computer vision applicatio...

Figures do matter: A literature review of 4587 robotic pancreatic resections and their implications on training.

BACKGROUND: The use of robotic assistance in minimally invasive pancreatic resection is quickly grow...

COVID-19 diagnosis via chest X-ray image classification based on multiscale class residual attention.

Aiming at detecting COVID-19 effectively, a multiscale class residual attention (MCRA) network is pr...

SiamOT: An Improved Siamese Network with Online Training for Visual Tracking.

As a prevailing solution for visual tracking, Siamese networks manifest high performance via convolu...

Design of Psychological Well-Being Education Environment Scheme Based on Deep Learning Theory.

This paper discusses the structure of psychological well-being education programmes in higher educat...

Learning From Synthetic CT Images via Test-Time Training for Liver Tumor Segmentation.

Automatic liver tumor segmentation could offer assistance to radiologists in liver tumor diagnosis, ...

A Gradient-Guided Evolutionary Approach to Training Deep Neural Networks.

It has been widely recognized that the efficient training of neural networks (NNs) is crucial to cla...

Local Critic Training for Model-Parallel Learning of Deep Neural Networks.

In this article, we propose a novel model-parallel learning method, called local critic training, wh...

Machine learning models to prognose 30-Day Mortality in Postoperative Disseminated Cancer Patients.

Patients with disseminated cancer at higher risk for postoperative mortality see improved outcomes w...

TAFM: A Recommendation Algorithm Based on Text-Attention Factorization Mechanism.

The click-through rate (CTR) prediction task is used to estimate the probabilities of users clicking...

Enhancing MR image segmentation with realistic adversarial data augmentation.

The success of neural networks on medical image segmentation tasks typically relies on large labeled...

Polyp segmentation with consistency training and continuous update of pseudo-label.

Polyp segmentation has accomplished massive triumph over the years in the field of supervised learni...