Jun Zhang

Difficulty-Aware Multi-Teacher Knowledge Distillation with Online Training-Sample Routing for Image Classification

Avinash Rajendra, Jun Zhang, Md Tauhidur Rahman

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Difficulty-Aware Multi-Teacher Knowledge Distillation with Online Training-Sample Routing for Image Classification

Avinash Rajendra, Jun Zhang, Md Tauhidur Rahman

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PrevCardioOncAI: Machine Learning Algorithms for Predicting Cardiovascular Disease in Cancer Survivors

Sherry-Ann N. Brown, Michelle Z. Fang, Rodney Sparapani, Yadi Zhou et autres

BACKGROUND: Cardiovascular disease (CVD) is a leading cause of death in cancer survivors. Predicting CVD risk in this population remains challenging. Risk prediction models that use machine learning algorithms could provide an objective method for accurate risk prediction to facilitate the prevention …

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MSWAFFNet: improved segmentation of nucleus using feature fusion of multi scale wavelet attention

Jun Zhang, Yangsheng Hu, Zhenzhou An

Introduction Nucleus segmentation plays an essential role in digital pathology,particularly in cancer diagnosis and the evaluation of treatment efficacy. Accurate nucleus segmentation provides critical guidance for pathologists. However, due to the wide variability instructure, color, and morphology of nuclei in histopathological images, …

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Multi-Length Skills with Priors for Reinforcement Learning

Carlos Ivan Jerez, Jun Zhang

Leveraging prior experience has been effective in accelerating reinforcement learning (RL). One approach for leveraging prior experience consists of learning skills, which are temporally extended sequences of actions, and priors over those skills, which are then used to learn new tasks. Existing …

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Research on Anomaly Detection of Ship Behavior Based on Data Mining

Jun Zhang, Enze Wu, Taizhi Lv

With the increase in the number of ships and the intensifying maritime traffic, maritime accidents such as ship collisions and grounding occur frequently, posing serious threats to people's lives and property. Therefore, timely detection and correction of abnormal ship behaviors are of …

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A Short Term Wind-Photovoltaic-Load Forecasting Model Based on Coupling Relationship and Multi-Layer Extraction Multi-Task Learning

Fu Sheng Yang, Jun Zhang, Zhiqiang Wang, Chunpeng Wang

The integration of renewable energy into the grid has deepened the uncertainty of the power system and brought difficulties to the economic dispatch of the power system. A better response is to accurately predict the Wind power, Photovoltaic power and Load power, …

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Cutting model integrated digital twin–based process monitoring in small-batch machining

Lele Bai, Jun Zhang, Jiaxing Yan, Luís Norberto López de Lacalle et autres

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TextureWGAN: texture preserving WGAN with multitask regularizer for computed tomography inverse problems

Masaki Ikuta, Jun Zhang

Purpose: This paper presents a deep learning (DL) based method called TextureWGAN. It is designed to preserve image texture while maintaining high pixel fidelity for computed tomography (CT) inverse problems. Over-smoothed images by postprocessing algorithms have been a well-known problem in the …

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Using Explainable Artificial Intelligence to Identify Key Characteristics of Deep Poverty for Each Household

Wenguang Zhang, Ting Lei, Yu Gong, Jun Zhang et autres

The first task for eradicating poverty is accurate poverty identification. Deep poverty identification is conducive to investing resources to help deeply poor populations achieve prosperity, one of the most challenging tasks in poverty eradication. This study constructs a deep poverty identification model …

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On Equivalence of Anomaly Detection Algorithms

Carlos Ivan Jerez, Jun Zhang, Marcia R. Silva

In most domains, anomaly detection is typically cast as an unsupervised learning problem because of the infeasibility of labeling large datasets. In this setup, the evaluation and comparison of different anomaly detection algorithms is difficult. Although some work has been published in …

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A Deep Convolutional Gated Recurrent Unit for CT Image Reconstruction

Masaki Ikuta, Jun Zhang

Computed tomography (CT) is one of the most important medical imaging technologies in use today. Most commercial CT products use a technique known as the filtered backprojection (FBP) that is fast and can produce decent image quality when an X-ray dose is …

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