2017 21st Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES)最新文献

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Selective decentralization to improve reinforcement learning in unknown linear noisy systems 选择性去中心化改进未知线性噪声系统的强化学习
2017 21st Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES) Pub Date : 2017-11-01 DOI: 10.1109/IESYS.2017.8233565
Thanh Nguyen, S. Mukhopadhyay
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引用次数: 1
Automatic skin lesion analysis towards melanoma detection 面向黑色素瘤检测的皮肤病变自动分析
2017 21st Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES) Pub Date : 2017-11-01 DOI: 10.1109/IESYS.2017.8233570
Le Thu Thao, N. Quang
{"title":"Automatic skin lesion analysis towards melanoma detection","authors":"Le Thu Thao, N. Quang","doi":"10.1109/IESYS.2017.8233570","DOIUrl":"https://doi.org/10.1109/IESYS.2017.8233570","url":null,"abstract":"Deep learning methods for image analysis have shown impressive performance in recent years. In this paper, we present deep learning based approaches to solve two problems in skin lesion analysis using a dermoscopic image containing skin tumor. In the first problem, we use a fully convolutional-deconvolutional architecture to automatically segment skin tumor from the surrounding skin. In the second problem, we use a simple convolutional neural network and VGG-16 architecture using transfer learning to address the two different tasks in skin tumor classification. The proposed models are trained and evaluated on standard benchmark datasets from the International Skin Imaging Collaboration (ISIC) 2017 Challenge, which consists of 2000 training samples and 600 testing samples. The result shows that the proposed methods achieve promising performances. In the first problem, the average value of Jaccard index for lesion segmentation using fully convolutional-deconvolutional architecture is 0.507. In the second problem, the values of area under the receiver operating characteristic curve (AUC) on two different lesion classifications using VGG16 with transfer learning are 0.763 and 0.869, respectively; the average value of AUC in two tasks is 0.816.","PeriodicalId":429982,"journal":{"name":"2017 21st Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131590817","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: 60
Reducing code bloat in Genetic Programming based on subtree substituting technique 基于子树替换技术的遗传规划代码缩减
2017 21st Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES) Pub Date : 2017-11-01 DOI: 10.1109/IESYS.2017.8233556
Thi Huong Chu, Quang Uy Nguyen
{"title":"Reducing code bloat in Genetic Programming based on subtree substituting technique","authors":"Thi Huong Chu, Quang Uy Nguyen","doi":"10.1109/IESYS.2017.8233556","DOIUrl":"https://doi.org/10.1109/IESYS.2017.8233556","url":null,"abstract":"Code bloat is a phenomenon in Genetic Programming (GP) that increases the size of individuals during the evolutionary process. Over the years, there has been a large number of research that attempted to address this problem. In this paper, we propose a new method to control code bloat and reduce the complexity of the solutions in GP. The proposed method is called Substituting a subtree with an Approximate Terminal (SAT-GP). The idea of SAT-GP is to select a portion of the largest individuals in each generation and then replace a random subtree in every individual in this portion by an approximate terminal of the similar semantics. SAT-GP is tested on twelve regression problems and its performance is compared to standard GP and the latest bloat control method (neat-GP). The experimental results are encouraging, SAT-GP achieved good performance on all tested problems regarding to the four popular performance metrics in GP research.","PeriodicalId":429982,"journal":{"name":"2017 21st Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116957859","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
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