the proceedings contain 32 papers. the topics discussed include: intelligent path planning of mobile robot based on genetic algorithm;accuracy improvement based on classic neural network: voting, restarting and quanti...
the proceedings contain 32 papers. the topics discussed include: intelligent path planning of mobile robot based on genetic algorithm;accuracy improvement based on classic neural network: voting, restarting and quantization;two applications of manifold regularization in deep learning architectures;an automatic wound detection system empowered by deep learning;data generation using simulation technology to improve perception mechanism of autonomous vehicles;detection of ischemic brain stroke using deep learning;self-supervised approach to addressing zero-shot learning problem;fault diagnosis of high-speed railway turnout system based on improved group decision-making;machine learning and deep learning methods on breast cancer metastases detection;turnout failure diagnosis system based on group decision making strategy;and improved causal Bayesian optimization algorithm with counter-noise acquisition function and supervised prior estimation.
Causality is an important element in decision-making and interventions are required to optimize results of target values. In this paper, based on the model of Causal Bayesian Optimization, a counter-noise version of a...
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Urban pavement disease recognition is for the most part, a mission performed manually. Recently, video analysis task has been one of the most important applications in various fields. Aims to renovate on the automated...
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this paper is an attempt to apply 3DUnet system to medical image segmentation. the classifying model is built based on actual medical images from MSD Cardiac dataset. the 3DUnet system, which is developed on Convoluti...
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Predicting ICU inpatients mortality index needs to be improved to incorporate clinical data. It is also helpful to reflect the patient's recovery and hospitals standards. In this research machine learning model Li...
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Recommender system suffers from huge selection bias from users, which makes utilizing causal inference to solve this problem becomes a necessary problem. However, traditional rating model only utilizing biased dataset...
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Now securing data in the cloud has become more complicated. In cloud environments, the data security based on the concept of authentication using cryptographic techniques is being checked. In addition to traditional e...
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In nowadays recommender system field. the selection bias is ubiquitous to most of the data. Most real-world rating data is sparse and missing not at random (MNAR). MNAR data make it difficult to accurately estimate th...
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As a widely discussed issue in academic and industrial fields, multiple object tracking (MOT) has a huge impact on various aspects, such as video surveillance, human-machine interaction, viral reality and autonomous d...
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there is a lot of room for research in how to detect breast cancer metastases in whole slide images more quickly and precisely. this work contrasts several machine learning and deep learning models on the breast cance...
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