2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS)最新文献_第2页

Machine Learning based Movement Analysis and Correction for Table Tennis1 基于机器学习的乒乓球运动分析与校正

2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS) Pub Date : 2022-11-26 DOI: 10.1109/ccis57298.2022.10016423

Xinzhu Qiu, Hao Zhang, Jiangning Wei, Jun Liu

引用次数: 0

PREVAIL: Pre-trained Variational Adversarial Active Learning for Molecular Property Prediction 占上风:分子性质预测的预训练变分对抗主动学习

2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS) Pub Date : 2022-11-26 DOI: 10.1109/CCIS57298.2022.10016422

Linjie Li, Yi Xiao, Dewei Ma, Kai Zheng

{"title":"PREVAIL: Pre-trained Variational Adversarial Active Learning for Molecular Property Prediction","authors":"Linjie Li, Yi Xiao, Dewei Ma, Kai Zheng","doi":"10.1109/CCIS57298.2022.10016422","DOIUrl":"https://doi.org/10.1109/CCIS57298.2022.10016422","url":null,"abstract":"Molecular property prediction is a fundamental task in drug discovery. The majority of the high-performing molecular property prediction methods currently were developed using deep learning techniques, which rely on massive labeled data. However, accurate molecular property annotation is time-consuming and expensive. Due to the fact that different samples usually have unequal importance in model training, we propose a pre-trained variational adversarial active learning, PREVAIL for short, to query the most informative samples to be annotated to reduce the annotation cost. Specifically, different from previous active learning whose initial set is sampled randomly, PREVAIL selects the most informative initial dataset by an autoencoder and K-Center greedy algorithm, which can avoid biases that affect the accuracy of the early decision-making process. Furthermore, PREVAIL simultaneously adapts the distribution of molecules and the information of the prediction task by incorporating the loss information of the molecular property prediction task into the latent space using task-aware variational adversarial active learning. Our benchmark experiments demonstrate that PREVAIL outperforms state-of-the-art active learning methods on molecular property prediction tasks.","PeriodicalId":374660,"journal":{"name":"2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122693038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DADR: Deep adaptive dimensionality reduction architecture based on the coefficient of variation DADR:基于变异系数的深度自适应降维架构

2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS) Pub Date : 2022-11-26 DOI: 10.1109/ccis57298.2022.10016418

Xuemei Ding, Jielei Chu, Dao Xiang, Tianrui Li

引用次数: 1

Global Interest Transfer Guided Session-based Recommendation 全球利益转移指导会议为基础的建议

2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS) Pub Date : 2022-11-26 DOI: 10.1109/CCIS57298.2022.10016408

Shukang Si, Shengming Guo, Xiao Xu, Hang Yu, Xiangfeng Luo

{"title":"Global Interest Transfer Guided Session-based Recommendation","authors":"Shukang Si, Shengming Guo, Xiao Xu, Hang Yu, Xiangfeng Luo","doi":"10.1109/CCIS57298.2022.10016408","DOIUrl":"https://doi.org/10.1109/CCIS57298.2022.10016408","url":null,"abstract":"Session-based recommendation aims to predict the next item based on the anonymous user’s clicked item sequence. Users’ interest in different content shifts regularly, and almost all of the current session based recommendation methods can’t capture the transfer relationship between interests, which can guide our prediction of the next item. This paper proposes an innovative method called Global Interest Transfer Guided Session based Recommendation(GITG), which uses global information to learn interest representations and transfer rules between interests to help the recommendation. In GITG, we parse sessions from two perspectives: (i)Interest: we learn the items’ interest representation by using the global neighbor set and learn the interests transfer relationship in the interest graph. (ii)Session: we learn the local embedding in the session graph and combine it with the global-post embedding. From these two perspectives, we can obtain interest representation and session representation, which provide high-value information for recommendation. Experiments show that GITG performs well on three real-world datasets.","PeriodicalId":374660,"journal":{"name":"2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115356328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Emotion Recognition Method based on Guided Fusion of Facial Expression and Bodily Posture 基于面部表情和身体姿势引导融合的情绪识别方法

2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS) Pub Date : 2022-11-26 DOI: 10.1109/ccis57298.2022.10016324

Zhong Huang, Danni Zhang, Fuji Ren, Min Hu, Liu Juan

引用次数: 0

A method of vehicle trajectory restoration based on Kalman Filter 一种基于卡尔曼滤波的车辆轨迹恢复方法

2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS) Pub Date : 2022-11-26 DOI: 10.1109/ccis57298.2022.10016320

Jiaming Sun, Xu Sun, Zhonghan Zhan, Jiaxu Zhou

引用次数: 0

Realization of tree and grass recognition based on AlexNet 基于AlexNet的树木和草地识别的实现

2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS) Pub Date : 2022-11-26 DOI: 10.1109/ccis57298.2022.10016438

Wang Yun-Zhou, Zhu Min-Ling, Chen Lei, Zhao Peng, Liu Hao-Nan, Xu Bo-Lang

引用次数: 0

Automated Plagiarism Detection Model Based On Deep Siamese Network 基于深度暹罗网络的自动抄袭检测模型

2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS) Pub Date : 2022-11-26 DOI: 10.1109/ccis57298.2022.10016354

Jing Zhang, Siyuan Xue, Jierui Li, Jian She

引用次数: 0

VQ-ViCNet: Strengthen Unique Features Comparison Autoencoder with Embedding Space for Covid-19 Image Classification VQ-ViCNet:基于嵌入空间的Covid-19图像分类增强独特特征比较自编码器

2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS) Pub Date : 2022-11-26 DOI: 10.1109/CCIS57298.2022.10016338

Qide Liu, Jielei Chu, Hua Yu, Xinlei Wang, Tianrui Li

引用次数: 0

Automatic Container Recognition and Positioning Method Based on Hough Transform and Mask RCNN 基于Hough变换和掩模RCNN的集装箱自动识别与定位方法

2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS) Pub Date : 2022-11-26 DOI: 10.1109/ccis57298.2022.10016394

Jingxuan Shao, Yong Zhou, Wen-Feng Li, Guodong Wang

{"title":"Automatic Container Recognition and Positioning Method Based on Hough Transform and Mask RCNN","authors":"Jingxuan Shao, Yong Zhou, Wen-Feng Li, Guodong Wang","doi":"10.1109/ccis57298.2022.10016394","DOIUrl":"https://doi.org/10.1109/ccis57298.2022.10016394","url":null,"abstract":"In multimodal transport, accurate identification and positioning of container is the key to construct container yard map. However, container recognition accuracy is low and vulnerable to the environment using the traditional Hough Transform. This paper proposes a container automatic recognition and positioning method based on Hough Transform and Mask Region-based Convolutional Neural Network (Mask RCNN) algorithm. The method consists of two parts, pre-processing of container images and instance segmentation using Mask RCNN algorithm. In the pre-processing part, Hough Transform is used to detect the polygon contour lines of the container image, and then the contour lines are filtered according to the container contour features to locate the container initially. In the segmentation part, using Mask RCNN algorithm, container features are detected for the pixels within the target contour line to identify the upper surface contour of the container, thus the exact location of the container is determined. The experimental results show that the method improves the recognition effect of traditional image processing algorithms and increases the stability and accuracy of container recognition and positioning.","PeriodicalId":374660,"journal":{"name":"2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS)","volume":"125 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116436049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0