Work Force

Mining Data Impressions From Deep Models as Substitute for the Unavailable Training Data.

Pretrained deep models hold their learnt knowledge in the form of model parameters. These parameters...

Large-Scale Distributed Training of Transformers for Chemical Fingerprinting.

Transformer models have become a popular choice for various machine learning tasks due to their ofte...

Cloud Computing Image Processing Application in Athlete Training High-Resolution Image Detection.

The rapid development of Internet of things mobile application technology and artificial intelligenc...

Perception without preconception: comparison between the human and machine learner in recognition of tissues from histological sections.

Deep neural networks (DNNs) have shown success in image classification, with high accuracy in recogn...

Ensemble classification combining ResNet and handcrafted features with three-steps training.

This work presents an ECG classifier for variable leads as a contribution to the Computing in Cardio...

A Deep Neural Network-Based Model for Quantitative Evaluation of the Effects of Swimming Training.

This paper analyzes the quantitative assessment model of the swimming training effect based on the d...

Early Prediction of Diabetes Using an Ensemble of Machine Learning Models.

Diabetes is one of the most rapidly spreading diseases in the world, resulting in an array of signif...

Prediction Models for Railway Track Geometry Degradation Using Machine Learning Methods: A Review.

Keeping railway tracks in good operational condition is one of the most important tasks for railway ...

Primary Investigation of Deep Learning Models for Japanese "Group Classification" of Whole-Slide Images of Gastric Endoscopic Biopsy.

BACKGROUND: Accurate pathological diagnosis of gastric endoscopic biopsy could greatly improve the o...

Study of Intelligent Wireless Network Management in the Context of Artificial Intelligence for the Improvement of Chinese Language Mandarin Test Training Programmes.

One of the most prominent ways of communication between people is through language, which plays a si...

Revisiting dose and intensity of training: Opportunities to enhance recovery following stroke.

PURPOSE: Stroke is a global leading cause of adult disability with survivors often enduring persiste...

Self-supervised graph neural network with pre-training generative learning for recommendation systems.

The case assignment system is an essential system of case management and assignment within the procu...

Training Deep Learning Models to Work on Multiple Devices by Cross-Domain Learning with No Additional Annotations.

PURPOSE: To create an unsupervised cross-domain segmentation algorithm for segmenting intraretinal f...

Recover User's Private Training Image Data by Gradient in Federated Learning.

Exchanging gradient is a widely used method in modern multinode machine learning system (e.g., distr...

Quantization-aware training for low precision photonic neural networks.

Recent advances in Deep Learning (DL) fueled the interest in developing neuromorphic hardware accele...

Machine Learning approach to Predict net radiation over crop surfaces from global solar radiation and canopy temperature data.

As the ground-based instruments for measuring net radiation are costly and need to be handled skillf...

Internet of Things (IoT) Enables Robot-Assisted Therapy as a Home Program for Training Upper Limb Functions in Chronic Stroke: A Randomized Control Crossover Study.

OBJECTIVE: To compare the effects of using an Internet of things (IoT)-assisted tenodesis-induced-gr...

Evaluation Method of Public Physical Training Quality Based on Global Topology Optimization Deep Learning Model.

In the quality evaluation of public sports training, the selected indicators are not comprehensive, ...

Endoscopy Training in the Age of Artificial Intelligence: Deep Learning or Artificial Competence?

Effective Training of Convolutional Neural Networks With Low-Bitwidth Weights and Activations.

This paper tackles the problem of training a deep convolutional neural network of both low-bitwidth ...

Hybrid robot-assisted gait training for motor function in subacute stroke: a single-blind randomized controlled trial.

BACKGROUND: Robot-assisted gait training (RAGT) is a practical treatment that can complement convent...