2017 IEEE Congress on Evolutionary Computation (CEC)最新文献_第3页

A multi-objective approach for calibration and detection of cervical cells nuclei 宫颈细胞核校正与检测的多目标方法

2017 IEEE Congress on Evolutionary Computation (CEC) Pub Date : 2017-06-05 DOI: 10.1109/CEC.2017.7969586

Paulo H. C. Oliveira, G. Moreira, D. Sabino, C. Carneiro, F. Medeiros, Flávio H. D. Araújo, Romuere R. V. Silva, A. G. Bianchi

{"title":"A multi-objective approach for calibration and detection of cervical cells nuclei","authors":"Paulo H. C. Oliveira, G. Moreira, D. Sabino, C. Carneiro, F. Medeiros, Flávio H. D. Araújo, Romuere R. V. Silva, A. G. Bianchi","doi":"10.1109/CEC.2017.7969586","DOIUrl":"https://doi.org/10.1109/CEC.2017.7969586","url":null,"abstract":"The automation process of Pap smear analysis holds the potential to address women's health care in the face of an increasing population and respective collected data. A fundamental step for automating analysis is cell detection from light microscopy images. Such information serves as input to cell classification algorithms and diagnostic recommendation tools. This paper describes an approach to nuclei cell segmentation, which critically impacts the following steps for cell analyses. We developed an algorithm combining clustering and genetic algorithms to detect image regions with high diagnostic value. A major problem when performing the segmentation of images is the cellular overlay. We introduce a new nuclear targeting approach using heuristics associated with a multi-objective genetic algorithm. Our experiments show results using a public 45-image dataset, including comparison to other cell detection approaches. The findings suggest an improvement in the nuclei segmentation and promise to support more sophisticated schemes for data quality control.","PeriodicalId":335123,"journal":{"name":"2017 IEEE Congress on Evolutionary Computation (CEC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122604639","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: 13

Data augmentation and evolutionary algorithms to improve the prediction of blood glucose levels in scarcity of training data 在训练数据匮乏的情况下，改进血糖水平预测的数据增强和进化算法

2017 IEEE Congress on Evolutionary Computation (CEC) Pub Date : 2017-06-05 DOI: 10.1109/CEC.2017.7969570

J. M. Velasco, O. Garnica, Sergio Contador, J. Lanchares, E. Maqueda, M. Botella, J. Hidalgo

{"title":"Data augmentation and evolutionary algorithms to improve the prediction of blood glucose levels in scarcity of training data","authors":"J. M. Velasco, O. Garnica, Sergio Contador, J. Lanchares, E. Maqueda, M. Botella, J. Hidalgo","doi":"10.1109/CEC.2017.7969570","DOIUrl":"https://doi.org/10.1109/CEC.2017.7969570","url":null,"abstract":"Diabetes Mellitus Type 1 patients are waiting for the arrival of the Artificial Pancreas. Artificial Pancreas systems will control the blood glucose of patients, improving their quality of life and reducing the risks they face daily. At the core of the Artificial Pancreas, an algorithm will forecast future glucose levels and estimate insulin bolus sizes. Grammatical Evolution has been proved as a suitable algorithm for predicting glucose levels. Nevertheless, one of the main obstacles that researches have found for training the Grammatical Evolution models is the lack of significant amounts of data. As in many other fields in medicine, the collection of data from real patients is very complex along with the fact that the patient's response can vary in a high degree due to a lot of personal factors which can be seen as different scenarios. In this paper, we propose both a classification system for scenario selection and a data augmentation algorithm that generates synthetic glucose time series from real data. Our experimental results show that, in a scarce data context, Grammatical Evolution models can get more accurate and robust predictions using scenario selection and data augmentation.","PeriodicalId":335123,"journal":{"name":"2017 IEEE Congress on Evolutionary Computation (CEC)","volume":"396 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134212900","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: 13

The effect of evaluation time variance on asynchronous Particle Swarm Optimization 评价时间方差对异步粒子群优化的影响

2017 IEEE Congress on Evolutionary Computation (CEC) Pub Date : 2017-06-05 DOI: 10.1109/CEC.2017.7969309

K. Holladay, K. Pickens, Gregory Miller

引用次数: 4

Decomposition Based Evolutionary Algorithm with a Dual Set of reference vectors 基于分解的双参考向量进化算法

2017 IEEE Congress on Evolutionary Computation (CEC) Pub Date : 2017-06-05 DOI: 10.1109/CEC.2017.7969302

Kalyan Shankar Bhattacharjee, H. Singh, T. Ray, Qingfu Zhang

{"title":"Decomposition Based Evolutionary Algorithm with a Dual Set of reference vectors","authors":"Kalyan Shankar Bhattacharjee, H. Singh, T. Ray, Qingfu Zhang","doi":"10.1109/CEC.2017.7969302","DOIUrl":"https://doi.org/10.1109/CEC.2017.7969302","url":null,"abstract":"Decomposition based approaches are increasingly being used to solve many-objective optimization problems (MaOPs). In such approaches, the MaOP is decomposed into several single-objective sub-problems and solved simultaneously guided by a set of predefined, uniformly distributed reference vectors. The reference vectors are constructed by joining a set of uniformly sampled points to the ideal point. Use of such reference vectors originating from the ideal point has so far performed reasonably well on common benchmarks such as DTLZs and WFGs, since the geometry of their Pareto fronts can be easily mapped using these reference vectors. However, the approach may not deliver a set of well distributed solutions for problems with Pareto fronts which are convex/concave or where the shape of the Pareto front is not best suited for such set of reference vectors (e.g. minus series of DTLZ and WFG test problems). While the notion of reference vectors originating from the nadir point has been suggested in the literature in the past, they have rarely been used in decomposition based algorithms. Such reference vectors are complementary in nature with the ones originating from the ideal point. Therefore, in this paper, we introduce a decomposition based approach which attempts to use both these two sets of reference vectors and chooses the most appropriate set at each generation based on the s-energy metric. The performance of the approach is presented and objectively compared with a number of recent algorithms. The results clearly highlight the benefits of such an approach especially when the nature of the Pareto front is not known a priori.","PeriodicalId":335123,"journal":{"name":"2017 IEEE Congress on Evolutionary Computation (CEC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134549593","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: 17

Multi-objective evolution of hash functions for high speed networks 高速网络哈希函数的多目标演化

2017 IEEE Congress on Evolutionary Computation (CEC) Pub Date : 2017-06-05 DOI: 10.1109/CEC.2017.7969485

David Grochol, L. Sekanina

引用次数: 4

A parallel Ant Colony System based on region decomposition for Taxi-Passenger Matching 基于区域分解的并行蚁群系统出租车乘客匹配

2017 IEEE Congress on Evolutionary Computation (CEC) Pub Date : 2017-06-05 DOI: 10.1109/CEC.2017.7969412

Xin Situ, Wei-neng Chen, Yue-jiao Gong, Ying Lin, Wei-jie Yu, Zhiwen Yu, Jun Zhang

引用次数: 7

A NSGA-II-based approach for service resource allocation in Cloud 一种基于nsga - ii的云服务资源分配方法

2017 IEEE Congress on Evolutionary Computation (CEC) Pub Date : 2017-06-05 DOI: 10.1109/CEC.2017.7969618

Boxiong Tan, Hui Ma, Yi Mei

引用次数: 23

Change detection in SAR images based on the salient map guidance and an accelerated genetic algorithm 基于显著图制导和加速遗传算法的SAR图像变化检测

2017 IEEE Congress on Evolutionary Computation (CEC) Pub Date : 2017-06-05 DOI: 10.1109/CEC.2017.7969436

Caihong Mu, Chengzhou Li, Yi Liu, Menghua Sun, L. Jiao, R. Qu

{"title":"Change detection in SAR images based on the salient map guidance and an accelerated genetic algorithm","authors":"Caihong Mu, Chengzhou Li, Yi Liu, Menghua Sun, L. Jiao, R. Qu","doi":"10.1109/CEC.2017.7969436","DOIUrl":"https://doi.org/10.1109/CEC.2017.7969436","url":null,"abstract":"This paper proposes a change detection algorithm in synthetic aperture radar (SAR) images based on the salient image guidance and an accelerated genetic algorithm (S-aGA). The difference image is first generated by logarithm ratio operator based on the bi-temporal SAR images acquired in the same region. Then a saliency detection model is applied in the difference image to extract the salient regions containing the changed class pixels. The salient regions are further divided by fuzzy c-means (FCM) clustering algorithm into three categories: changed class (set of pixels with high gray values), unchanged class (set of pixels with low gray values) and undetermined class (set of pixels with middle gray value, which are difficult to classify). Finally, the proposed accelerated GA is applied to explore the reduced search space formed by the undetermined-class pixels according to an objective function considering neighborhood information. In S-aGA, an efficient mutation operator is designed by using the neighborhood information of undetermined-class pixels as the heuristic information to determine the mutation probability of each undetermined-class pixel adaptively, which accelerates the convergence of the GA significantly. The experimental results on two data sets demonstrate the efficiency of the proposed S-aGA. On the whole, S-aGA outperforms five other existing methods including the simple GA in terms of detection accuracy. In addition, S-aGA could obtain satisfying solution within limited generations, converging much faster than the simple GA.","PeriodicalId":335123,"journal":{"name":"2017 IEEE Congress on Evolutionary Computation (CEC)","volume":"80 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123141315","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: 10

A multi-agent genetic algorithm for improving the robustness of communities in complex networks against attacks 一种用于提高复杂网络社区抗攻击鲁棒性的多智能体遗传算法

2017 IEEE Congress on Evolutionary Computation (CEC) Pub Date : 2017-06-05 DOI: 10.1109/CEC.2017.7969290

Shuai Wang, Jing Liu

引用次数: 3

New Artificial Intelligence approaches for future UAV Ground Control Stations 未来无人机地面控制站的新人工智能方法

2017 IEEE Congress on Evolutionary Computation (CEC) Pub Date : 2017-06-05 DOI: 10.1109/CEC.2017.7969645

Cristian Ramírez-Atencia, V. Rodríguez-Fernández, A. González-Pardo, David Camacho

{"title":"New Artificial Intelligence approaches for future UAV Ground Control Stations","authors":"Cristian Ramírez-Atencia, V. Rodríguez-Fernández, A. González-Pardo, David Camacho","doi":"10.1109/CEC.2017.7969645","DOIUrl":"https://doi.org/10.1109/CEC.2017.7969645","url":null,"abstract":"The increasing interest in the use of Unmanned Aerial Vehicles (UAV) in the last years has opened up a new complex area of research applications. Many works have been focused on the applicability of new Artificial Intelligence techniques to facilitate the successfully execution of UAV operations from the Ground Control Stations (GCSs). Some of the most demanded applications in this field are the reduction of the workload of operators and the automation of training processes. This paper presents new algorithms focused on this field: a Multi-Objective Genetic Algorithm for solving Mission Planning and Replanning problems and a Procedure Following Evaluation methodology based on Petri Nets. This paper is based on a framework that simulates a GCS with support for multiple UAVs. The functionality of this framework has been extended in two different directions: on the one hand, to deal with Mission Designing, Automated Mission Planning and Replanning, and Alert Generation; and, on the other hand, to perform different analysis tasks of the UAV operators. Using this framework, a test mission has been executed and debriefed, focusing on the main AI-based issues described in this work.","PeriodicalId":335123,"journal":{"name":"2017 IEEE Congress on Evolutionary Computation (CEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130562026","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: 13