2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC)最新文献

Semantic spatial weighted regression for realizing spatial correlation of deforestation effect on soil degradation 语义空间加权回归实现森林砍伐对土壤退化影响的空间关联

2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC) Pub Date : 2017-12-19 DOI: 10.1109/KCIC.2017.8228566

Irene Erlyn Wina Rachmawan, Y. Kiyoki

引用次数: 0

A realtime sensing-data-triggered news article provision system with 5D world map 一个实时传感数据触发新闻文章提供系统与5D世界地图

2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC) Pub Date : 2017-12-19 DOI: 10.1109/KCIC.2017.8228597

Hanako Fujioka, S. Sasaki, Y. Kiyoki

引用次数: 0

Disaster detection from aerial imagery with convolutional neural network 基于卷积神经网络的航空图像灾害检测

2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC) Pub Date : 2017-12-19 DOI: 10.1109/KCIC.2017.8228593

S. Amit, Y. Aoki

{"title":"Disaster detection from aerial imagery with convolutional neural network","authors":"S. Amit, Y. Aoki","doi":"10.1109/KCIC.2017.8228593","DOIUrl":"https://doi.org/10.1109/KCIC.2017.8228593","url":null,"abstract":"In recent years, analysis of remote sensing imagery is imperatives in the domain of environmental and climate monitoring primarily for the application of detecting and managing a natural disaster. Satellite imagery or aerial imagery is beneficial because it can widely capture the condition of the surface ground and provides a massive amount of information in a piece of satellite imagery. Since obtaining satellite imagery or aerial imagery is getting more ease in recent years, landslide detection and flood detection is highly in demand. In this paper, we propose automatic natural disaster detection particularly for landslide and flood detection by implementing convolutional neural network (CNN) in extracting the feature of disaster more effectively. CNN is robust to shadow, able to obtain the characteristic of disaster adequately and most importantly able to overcome misdetection or misjudgment by operators, which will affect the effectiveness of disaster relief. The neural network consists of 2 phases: training phase and testing phase. We created training data patches of pre-disaster and post-disaster by clipping and resizing aerial imagery obtained from Google Earth Aerial Imagery. We are currently focusing on two countries which are Japan and Thailand. Training dataset for both landslide and flood consist of 50000 patches. All patches are trained in CNN to extract region where changes occurred or known as disaster region occurred without delay. We obtained accuracy of our system in around 80%–90% of both disaster detections. Based on the promising results, the proposed method may assist in our understanding of the role of deep learning in disaster detection.","PeriodicalId":117148,"journal":{"name":"2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128306594","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: 49

A fuzzy system for quality assurance of crowdsourced wildlife observation geodata 众包野生动物观测地理数据质量保证的模糊系统

2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC) Pub Date : 2017-12-19 DOI: 10.1109/KCIC.2017.8228563

H. Vahidi, Wanglin Yan, B. Klinkenberg

引用次数: 4

Feature selection using genetic algorithm to improve classification in network intrusion detection system 基于遗传算法的特征选择改进了网络入侵检测系统的分类

2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC) Pub Date : 2017-12-19 DOI: 10.1109/KCIC.2017.8228458

Andrey Ferriyan, A. Thamrin, K. Takeda, J. Murai

引用次数: 22

UAV-based multispectral aerial image retrieval using spectral feature and semantic computing 基于光谱特征和语义计算的无人机多光谱航拍图像检索

2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC) Pub Date : 2017-12-19 DOI: 10.1109/KCIC.2017.8228571

Jinmika Wijitdechakul, S. Sasaki, Y. Kiyoki, C. Koopipat

{"title":"UAV-based multispectral aerial image retrieval using spectral feature and semantic computing","authors":"Jinmika Wijitdechakul, S. Sasaki, Y. Kiyoki, C. Koopipat","doi":"10.1109/KCIC.2017.8228571","DOIUrl":"https://doi.org/10.1109/KCIC.2017.8228571","url":null,"abstract":"This research proposes the multispectral image retrieval method by using spectral feature and semantic computing which is not many studies have focused. The main contributions are to enhance the effectiveness and advantageous of global environmental analysis system and realize semantic associative search and analysis. In this work, we study multispectral image retrieval using spectral feature computed in multispectral semantic-image space. The multispectral semantic-image space is supposing to realize the interpretation of substance (materials) on earth surface which can be provided the analyzed results as human-level interpretation. Our essential approach is utilizing the semantic computing to measure the similarity between multispectral image and the meaningful keywords which according to the user's contexts. Our research results found that this method possible to acquire the spectral feature from the multispectral image and could be used in multispectral image retrieval. In this study, a multispectral image is used as the image query according to user's query contexts. Moreover, the method performance of UAV-based multispectral aerial image retrieval using spectral feature and semantic computing is measured based on the queries with three contexts of multispectral image which is indicated by previous study on agricultural monitoring system and semantic interpretation model.","PeriodicalId":117148,"journal":{"name":"2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126062490","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

Preliminary design of mobile visual programming apps for Internet of Things applications based on Raspberry Pi 3 platform 基于树莓派3平台的物联网应用移动可视化编程app初步设计

2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC) Pub Date : 2017-09-01 DOI: 10.1109/KCIC.2017.8228460

A. Besari, Iwan Kurnianto Wobowo, S. Sukaridhoto, Ricky Setiawan, Muh. Rifqi Rizqullah

{"title":"Preliminary design of mobile visual programming apps for Internet of Things applications based on Raspberry Pi 3 platform","authors":"A. Besari, Iwan Kurnianto Wobowo, S. Sukaridhoto, Ricky Setiawan, Muh. Rifqi Rizqullah","doi":"10.1109/KCIC.2017.8228460","DOIUrl":"https://doi.org/10.1109/KCIC.2017.8228460","url":null,"abstract":"Learning about sensor technology and actuator early is important as a step towards knowing and introducing of advanced technologies based on Internet of Things (IoT). The difficulties are how to learn sensor technology and move the actuator with accessing General Purpose Input Output (GPIO) of Raspberry Pi 3 Platforms using programming language syntax which often confusing and difficult to understand. To help people learning IoT by using Raspberry Pi 3 with an interesting Android apps, we believe that this learning module can integrate about the ease and attractiveness of IoT System Editor based on Android apps. This research create a mobile programming apps based on Android which people can build IoT project easily with GUI without program and middleware based on Raspberry Pi to connect between apps and hardware with especially task to manage data communication, data flow, and device driver. Hopefully new developer can develop the IoT application easily by using Android mobile visual programming that combined with Raspberry Pi 3 platform.","PeriodicalId":117148,"journal":{"name":"2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC)","volume":"157 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115986762","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

Aksara jawa text detection in scene images using convolutional neural network 基于卷积神经网络的场景图像Aksara java文本检测

2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC) Pub Date : 2017-09-01 DOI: 10.1109/KCIC.2017.8228567

M. L. Afakh, Anhar Risnumawan, M. Anggraeni, Mohamad Nasyir Tamara, E. S. Ningrum

{"title":"Aksara jawa text detection in scene images using convolutional neural network","authors":"M. L. Afakh, Anhar Risnumawan, M. Anggraeni, Mohamad Nasyir Tamara, E. S. Ningrum","doi":"10.1109/KCIC.2017.8228567","DOIUrl":"https://doi.org/10.1109/KCIC.2017.8228567","url":null,"abstract":"Aksara jawa is an ancient Javanese character, which has been used since 17th century. The character is mostly written on stones to describe history or naming such as places, wedding, tombstones, etc. This character is however gradually ignored by people. Thus, it is extremely important to preserve this near loss heritage culture. In this paper, as a step toward preserving and converting visual information into text, we develop Aksara Jawa text detection system in scene images employing deep convolutional neural network to localize the occurrence of Aksara Jawa text. This method mainly differs from the existing Aksara Jawa text works that employ manually hand-crafted features and explicitly learn a classifier. The features and classifier of this method are jointly learned from which the back-propagation technique is employed to obtain parameters simultaneously. A text confidence map is then produced followed by bounding boxes formation which is estimated and formed to indicate the occurrence of text lines. Experiments show encouraging result for the benefit of text analysis on Aksara Jawa.","PeriodicalId":117148,"journal":{"name":"2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116122670","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: 15

Multi-group particle swarm optimization with random redistribution 随机再分配的多群粒子群优化

2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC) Pub Date : 2017-09-01 DOI: 10.1109/KCIC.2017.8228445

Naufal Suryanto, C. Ikuta, D. Pramadihanto

引用次数: 3

Automatic lung cancer detection using color histogram calculation 使用颜色直方图计算的肺癌自动检测

2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC) Pub Date : 2017-09-01 DOI: 10.1109/KCIC.2017.8228574

R. Wulandari, R. Sigit, Setia Wardhana

引用次数: 7