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2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)最新文献

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ResNet-Based Model for Cancer Detection 基于resnet的癌症检测模型
2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2021-01-15 DOI: 10.1109/ICCECE51280.2021.9342346
Zhuo Zheng, Hao Zhang, Xinjian Li, Shuai Liu, Y. Teng
{"title":"ResNet-Based Model for Cancer Detection","authors":"Zhuo Zheng, Hao Zhang, Xinjian Li, Shuai Liu, Y. Teng","doi":"10.1109/ICCECE51280.2021.9342346","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342346","url":null,"abstract":"Cancer is a horrible disease and a major reason to cause death in the world. Early detection and diagnosis can help doctor save life. Many computer-aided diagnosis techniques use image processing to help doctor do cancer detection and obtain considerable achievements. In this paper, we propose a novel ResNet-based deep learning network to identify metastatic cancer from cancer scan images. Furthermore, we apply Test Time Augmentation to make our model more robust and improve detection accuracy. The results of experiments on a slightly modified version of the PatchCamelyon (PCam) benchmark dataset (the original PCam dataset contains duplicate images due to its probabilistic sampling, however, the version we use does not contain duplicates), which packs the clinically-relevant task of metastasis detection into a straightforward binary image classification task, indicates that the proposed ResNet-based model has achieved the state-of-the-art performance, which goes beyond performance of previous VGG16, VGG19 models.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129224374","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: 5
Information Security Practice of Intelligent Knowledge Ecological Communities with Cloud Computing 基于云计算的智能知识生态社区信息安全实践
2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2021-01-15 DOI: 10.1109/ICCECE51280.2021.9342141
Yingjue Ma, Hui-jun Ni, Yanping Li
{"title":"Information Security Practice of Intelligent Knowledge Ecological Communities with Cloud Computing","authors":"Yingjue Ma, Hui-jun Ni, Yanping Li","doi":"10.1109/ICCECE51280.2021.9342141","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342141","url":null,"abstract":"With powerful ability to organize, retrieve and share information, cloud computing technology has effectively improved the development of intelligent learning ecological Communities. The study finds development create a security atmosphere with all homomorphic encryption technology, virtualization technology to prevent the leakage and loss of information data. The result provided a helpful guideline to build a security environment for intelligent ecological communities.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117057548","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: 1
Valuation and Settlement of Power Electronics-based Flexible Loads: A Zhejiang Electricity Market Case Study 基于电力电子的柔性负荷计价与结算——以浙江电力市场为例
2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2021-01-15 DOI: 10.1109/ICCECE51280.2021.9342173
Jiahua Hu, Yang Xu, Xiangyu Ma, Zhiyi Li
{"title":"Valuation and Settlement of Power Electronics-based Flexible Loads: A Zhejiang Electricity Market Case Study","authors":"Jiahua Hu, Yang Xu, Xiangyu Ma, Zhiyi Li","doi":"10.1109/ICCECE51280.2021.9342173","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342173","url":null,"abstract":"As flexible power electronic equipment is gradually put into use on the load side, the load has become an important flexibility resource for the power system. The demand response market is the main platform for these resources to earn rewards. Currently, the Zhejiang demand response market is still in its infancy. The current demand response market mechanism in Zhejiang does not sufficiently reflect the value of flexible power electronic load participation in the demand response market. Based on the characteristics of the demand response market in Zhejiang province, we propose a market settlement mechanism for future large-scale flexible power electronic load participating in the Zhejiang demand response market. This model can effectively promote the healthy development of the demand response market in Zhejiang and improve the accuracy of demand response services.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120958060","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
Improve the Scale Invariance of the Convolutional Network for Crowd Counting 改进卷积网络在人群计数中的尺度不变性
2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2021-01-15 DOI: 10.1109/ICCECE51280.2021.9342331
Ryan Jin
{"title":"Improve the Scale Invariance of the Convolutional Network for Crowd Counting","authors":"Ryan Jin","doi":"10.1109/ICCECE51280.2021.9342331","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342331","url":null,"abstract":"The main challenges of crowd counting are considerable variations in complex scenes/backgrounds. This paper first reveals that the Convolution Neural Networks (CNNs) are incapable of addressing these problems. To solve this problem, we propose a novel attention mechanism to improve the scale invariance of convolutional networks. Our method can not only automatically exploit spatial awareness to optimize the convolutional features but also imitate the human attention mechanism to remove the noise of the background. It is worth noting that it can easily plug-and-play into the vanilla convolution/pooling layer with relatively little computation cost. We have integrated our method into several state-of-the-art methods. Extensive experiments on five popular benchmarks demonstrate that our approach significantly outperforms other state-of-the-art methods and beats entire convolution/pooling layer in all cases.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122451988","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
Sales Forecasting Using GBDT Based Model And Data Mining Method 基于GBDT模型和数据挖掘方法的销售预测
2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2021-01-15 DOI: 10.1109/ICCECE51280.2021.9342243
Yichun Zhou, Yu-shiuan Cheng, Yucheng Lin, Tian Mengqiu
{"title":"Sales Forecasting Using GBDT Based Model And Data Mining Method","authors":"Yichun Zhou, Yu-shiuan Cheng, Yucheng Lin, Tian Mengqiu","doi":"10.1109/ICCECE51280.2021.9342243","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342243","url":null,"abstract":"Accurately predicting the sales of the mall can help companies adjust production strategies in a timely manner, improve production efficiency, and improve competitiveness. This article is based on the LightGBM model to realize Wal-Mart’s sales forecast. Due to the large amount of data in the data set given by the material and the relatively messy data types, we first perform feature processing on the original data, unify the abnormal data, and extract the data features, so as to obtain the processed data that can be used for modeling. In the use of grid search algorithm for parameter selection. Experiments show that the root mean square error of the LightGBM model is only 2.07, which has better predictive performance compared with the traditional linear regression model and SVM model.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115429388","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
Multi-Robot Point Cloud Map Fusion Algorithm Based on Visual SLAM 基于视觉SLAM的多机器人点云图融合算法
2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2021-01-15 DOI: 10.1109/ICCECE51280.2021.9342251
Yanjiang Chen, Yanbo Wang, Junqin Lin, Zhihong Chen, Yao Wang
{"title":"Multi-Robot Point Cloud Map Fusion Algorithm Based on Visual SLAM","authors":"Yanjiang Chen, Yanbo Wang, Junqin Lin, Zhihong Chen, Yao Wang","doi":"10.1109/ICCECE51280.2021.9342251","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342251","url":null,"abstract":"To solve the problem of inaccurate judgment of overlapping areas in multi-robot system point cloud map fusion, an overlapping areas judgment method based on visual SLAM key frames relative motion size is mooted. On the basis of SLAM mapping, the relative motion is determined comprehensively through features matching and geometric constraint between key frames. Then overlapping areas of maps are determined by relative motion size. At last initial transformation matrix between maps can be calculated. We run our algorithm in both open datasets and real world environment. The results show that the accuracy of this algorithm is higher than that of traditional algorithms.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131488996","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
CWAI-CNER: Chinese entity recognition based on adaptive incorporation of characters and words cner:基于自适应字词合并的中文实体识别
2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2021-01-15 DOI: 10.1109/ICCECE51280.2021.9342310
Pai Peng, Xu Wu, Xiaqing Xie, Jingchen Wu
{"title":"CWAI-CNER: Chinese entity recognition based on adaptive incorporation of characters and words","authors":"Pai Peng, Xu Wu, Xiaqing Xie, Jingchen Wu","doi":"10.1109/ICCECE51280.2021.9342310","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342310","url":null,"abstract":"Chinese Named Entity Recognition (CNER) is an important sub topic in the field of Chinese Natural Language Processing, which plays an important role in multi tasks. However, it’s difficult to determine the boundaries of entities in Chinese texts because the Chinese words are not naturally separated, which further causes the task of CNER much more difficult. In addition, the mainstream Named Entity Recognition (NER) is based on sequence tagging, which causes the cost of training set labeling very high, so many NER tasks are limited by training sets’ deficiency. In this work, we propose a new CNER method based on adaptive incorporation of characters and words–CWAI to solve the problem of words information loss caused by lacking of words boundaries, which uses convolution neural network (CNN) to capture the local semantics for every character, and then adaptively calculates the weights of potential words that match a lexicon for each character based on attention mechanism between characters and words. And for the problem of limited model effects due to insufficient training set, we combined our model with pre-trained models to solve that.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131559821","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
Regularization model based on transmission constraint 基于传输约束的正则化模型
2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2021-01-15 DOI: 10.1109/ICCECE51280.2021.9342369
B. Xie, Zhiming Lv, Junxia Yang, Jianhao Shen
{"title":"Regularization model based on transmission constraint","authors":"B. Xie, Zhiming Lv, Junxia Yang, Jianhao Shen","doi":"10.1109/ICCECE51280.2021.9342369","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342369","url":null,"abstract":"Aiming at the problems of blocking and artifacts in traditional dark channel prior dehazing algorithms, an image dehazing algorithm based on dark channel priors is proposed. First, the transmission is corrected once according to the characteristics of the dark channel of the image to solve the block effect caused by the underestimation of the transmission. Secondly, in order to overcome the problem of blurring of details, this paper proposes a regularized model based on transmission correction to optimize transmission twice to overcome the artifact problem in traditional dehazing algorithms. In addition, the Alternating Direction Method of Multipliers (ADMM) is used to solve the new model. Finally, the atmospheric scattering model is used to restore the image. Numerical experimental results show that the proposed method is significantly better than the traditional image dehazing algorithm. Taking the $480times 540$ Boat image as an example, the PSNR and SSIM value of the method in the article are improved by 1. 8dB and 0. 56dB on average. The algorithm proposed in the article solves the blocking effect while eliminating the haze, and eliminates the artifacts of the image. It is significantly better than the traditional dehazing algorithm in terms of visual effects and objective evaluation indicators.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123731635","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: 1
Improving Septic Shock Prediction with AdaBoost and Cox Regression Model AdaBoost和Cox回归模型改进脓毒性休克预测
2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2021-01-15 DOI: 10.1109/ICCECE51280.2021.9342457
Aiman Darwiche, Ayman El-Geneidy, Sumitra Mukherjee
{"title":"Improving Septic Shock Prediction with AdaBoost and Cox Regression Model","authors":"Aiman Darwiche, Ayman El-Geneidy, Sumitra Mukherjee","doi":"10.1109/ICCECE51280.2021.9342457","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342457","url":null,"abstract":"Septic shock in the advanced state of sepsis, which is a dangerous organ dysfunction disease that happens when the body responds in a dysregulated way to infectious diseases. Sepsis is hard to discover early on, and is difficult to treat if not detected sooner, hence, leading to high mortality rates. The efforts to improve the methods for identifying septic shock is ongoing in the medical and computer science communities. This paper uses the MMIC-III database to create a model to effectively predict septic shock utilizing a combination of the Cox regression model and AdaBoost. The prediction model is constructed by acquiring a risk factor score using Cox regression on various septic shock indicators. The score was appended as a feature to a selected listing of indicators and the AdaBoost ensemble classifier was applied to deliver the model. The predictive accuracy of the Cox Enhanced AdaBoost (CEAB) model was compared to prominent models to evaluate its effectiveness.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117301316","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: 3
Research on Renewal Probability Problem of Applying Clustering Method Under Big Data 大数据下应用聚类方法的更新概率问题研究
2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2021-01-15 DOI: 10.1109/ICCECE51280.2021.9342508
Ying Miao, Xinlei Zhao, Jiankai Zuo, Zhongzhi Li, Yilin Yan, Jin Xie
{"title":"Research on Renewal Probability Problem of Applying Clustering Method Under Big Data","authors":"Ying Miao, Xinlei Zhao, Jiankai Zuo, Zhongzhi Li, Yilin Yan, Jin Xie","doi":"10.1109/ICCECE51280.2021.9342508","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342508","url":null,"abstract":"Under the wave of the big data era, we need to analyze some data sets that cannot be captured and processed with conventional software tools within a certain time frame with new processing modes, so as to obtain stronger decision-making power and insight. In view of this, this paper uses a big data pattern matching algorithm to establish a SOM network (Self-Organizing feature Map) to calculate the probability of auto insurance renewal under the background of complex data. On the one hand, this research will increase the insurance renewal rate. In addition, it can provide advice and reference for the cultivation of auto insurance customer loyalty under the epidemic situation, and has a certain reference role for the development of my country’s insurance digitalization.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"665 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115122569","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
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