Might be useful if your group decided to design such a mechanism.
\n", "tags": [], "relations": {}, "dateAdded": "2015-04-29T20:13:09Z", "dateModified": "2015-04-29T20:13:26Z" } }, { "key": "MV3EXMF3", "version": 4, "library": { "type": "group", "id": 347047, "name": "Satellite identification of rooftop PV", "links": { "alternate": { "href": "https://www.zotero.org/groups/satellite_identification_of_rooftop_pv", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/347047/items/MV3EXMF3", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/satellite_identification_of_rooftop_pv/items/MV3EXMF3", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1261598, "username": "Bibliobomb", "name": "Alex Hernandez", "links": { "alternate": { "href": "https://www.zotero.org/bibliobomb", "type": "text/html" } } }, "creatorSummary": "Arun and Katiyar", "parsedDate": "2013-12", "numChildren": 1 }, "data": { "key": "MV3EXMF3", "version": 4, "itemType": "journalArticle", "title": "An evolutionary computing frame work toward object extraction from satellite images", "creators": [ { "creatorType": "author", "firstName": "P. V.", "lastName": "Arun" }, { "creatorType": "author", "firstName": "S. K.", "lastName": "Katiyar" } ], "abstractNote": "Image interpretation domains have witnessed the application of many intelligent methodologies over the past decade; however the effective use of evolutionary computing techniques for feature detection has been less explored. In this paper, we critically analyze the possibility of using cellular neural network for accurate feature detection. Contextual knowledge has been effectively represented by incorporating spectral and spatial aspects using adaptive kernel strategy. Developed methodology has been compared with traditional approaches in an object based context and investigations revealed that considerable success has been achieved with the procedure. Intelligent interpretation, automatic interpolation, and effective contextual representations are the features of the system.", "publicationTitle": "The Egyptian Journal of Remote Sensing and Space Science", "publisher": "", "place": "", "date": "December 2013", "volume": "16", "issue": "2", "section": "", "partNumber": "", "partTitle": "", "pages": "163-169", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "The Egyptian Journal of Remote Sensing and Space Science", "DOI": "10.1016/j.ejrs.2013.05.003", "citationKey": "", "url": "http://www.sciencedirect.com/science/article/pii/S1110982313000197", "accessDate": "2015-04-29T20:13:05Z", "PMID": "", "PMCID": "", "ISSN": "1110-9823", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Cellular neural network", "type": 1 }, { "tag": "Feature detection", "type": 1 }, { "tag": "Interpolation", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2015-04-29T20:13:05Z", "dateModified": "2015-04-29T20:13:05Z" } }, { "key": "SMJ8Q72G", "version": 3, "library": { "type": "group", "id": 347047, "name": "Satellite identification of rooftop PV", "links": { "alternate": { "href": "https://www.zotero.org/groups/satellite_identification_of_rooftop_pv", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/347047/items/SMJ8Q72G", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/satellite_identification_of_rooftop_pv/items/SMJ8Q72G", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1261598, "username": "Bibliobomb", "name": "Alex Hernandez", "links": { "alternate": { "href": "https://www.zotero.org/bibliobomb", "type": "text/html" } } }, "creatorSummary": "Nian et al.", "parsedDate": "2010-09", "numChildren": 0 }, "data": { "key": "SMJ8Q72G", "version": 3, "itemType": "conferencePaper", "title": "Automatic Detection of Defects in Solar Modules: Image Processing in Detecting", "creators": [ { "creatorType": "author", "firstName": "Bei", "lastName": "Nian" }, { "creatorType": "author", "firstName": "Zhizhong", "lastName": "Fu" }, { "creatorType": "author", "firstName": "Li", "lastName": "Wang" }, { "creatorType": "author", "firstName": "Xiaoxuan", "lastName": "Cao" } ], "abstractNote": "Image acquisition devices which can get infrared image of solar modules is designed by using the principles of the semiconductor's electroluminescence, and image processing is applied to the detection system which can detect the defects automatically including black pieces, fragmentation, broken grid, crack and so on. At first the defects of the infrared image are classified and then the defects' types and locations are marked out after filtering, single-chip division, gray-scale transformation, binary, feature description and extraction, finally the results are feeded back to the database. This method increases the defects' types (such as invisible crack) which the manual testing is difficult to identify, it also can eliminate human errors which manual testing may produce possibly and can reduce labor costs, defects' rates, further it can improve the detection's efficiency and productivity of production line.", "proceedingsTitle": "2010 6th International Conference on Wireless Communications Networking and Mobile Computing (WiCOM)", "conferenceName": "2010 6th International Conference on Wireless Communications Networking and Mobile Computing (WiCOM)", "publisher": "", "place": "", "date": "Sept 2010", "eventPlace": "", "volume": "", "issue": "", "numberOfVolumes": "", "pages": "1-4", "series": "", "seriesNumber": "", "DOI": "10.1109/WICOM.2010.5600703", "ISBN": "", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "Automatic Detection of Defects in Solar Modules", "language": "", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Cameras", "type": 1 }, { "tag": "Computers", "type": 1 }, { "tag": "Conferences", "type": 1 }, { "tag": "Image recognition", "type": 1 }, { "tag": "Photovoltaic cells", "type": 1 }, { "tag": "automatic detection", "type": 1 }, { "tag": "black pieces", "type": 1 }, { "tag": "broken grid", "type": 1 }, { "tag": "crack", "type": 1 }, { "tag": "cracks", "type": 1 }, { "tag": "defects", "type": 1 }, { "tag": "detection system", "type": 1 }, { "tag": "fault diagnosis", "type": 1 }, { "tag": "feature description", "type": 1 }, { "tag": "feature extraction", "type": 1 }, { "tag": "fragmentation", "type": 1 }, { "tag": "gray-scale transformation", "type": 1 }, { "tag": "image acquisition devices", "type": 1 }, { "tag": "image processing", "type": 1 }, { "tag": "infrared image", "type": 1 }, { "tag": "semiconductor electroluminescence", "type": 1 }, { "tag": "single-chip division", "type": 1 }, { "tag": "solar cells", "type": 1 }, { "tag": "solar modules", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2015-04-29T19:57:14Z", "dateModified": "2015-04-29T19:57:14Z" } }, { "key": "CGPAANRB", "version": 2, "library": { "type": "group", "id": 347047, "name": "Satellite identification of rooftop PV", "links": { "alternate": { "href": "https://www.zotero.org/groups/satellite_identification_of_rooftop_pv", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/347047/items/CGPAANRB", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/satellite_identification_of_rooftop_pv/items/CGPAANRB", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1261598, "username": "Bibliobomb", "name": "Alex Hernandez", "links": { "alternate": { "href": "https://www.zotero.org/bibliobomb", "type": "text/html" } } }, "creatorSummary": "Suri et al.", "parsedDate": "2008-03", "numChildren": 0 }, "data": { "key": "CGPAANRB", "version": 2, "itemType": "journalArticle", "title": "Geographic Aspects of Photovoltaics in Europe: Contribution of the PVGIS Website", "creators": [ { "creatorType": "author", "firstName": "M.", "lastName": "Suri" }, { "creatorType": "author", "firstName": "T.", "lastName": "Huld" }, { "creatorType": "author", "firstName": "E.D.", "lastName": "Dunlop" }, { "creatorType": "author", "firstName": "T.", "lastName": "Cebecauer" } ], "abstractNote": "The photovoltaic geographic information system (PVGIS) is a web-based knowledge distribution system that provides climate data and tools needed for the performance assessment of photovoltaic (PV) technology in Europe. Geodatabases and simulation models are interlinked with the web interface, thus providing easy-to-use access to users. Interactive maps play an important role in understanding the geographic dependency of the performance of the PV technology. While our previous papers dealt with technical aspects of development and data analysis, here we review lessons learned from the feedback of users. A description of the underlying data and web tools is followed by the analysis of two points that are often discussed when comparing PVGIS with alternative systems: 1) the uncertainty of solar radiation estimates and 2) PV yield predictions. For systems based on the ground observations, such as PVGIS, higher uncertainty of estimates can be expected in mountains, close to the coastline, and in regions with lower density of the meteorological stations. A comparison of PVGIS with other simulation software may show regional differences, which typically reflect: 1) the use of underlying databases that are based on diverse input data (ground-measured or satellite with various observation periods) and that vary in spatial and time resolutions, and 2) the use of different simulation concepts. A cross comparison of the existing systems is needed to identify advantages and limits of their use in solar energy projects.", "publicationTitle": "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing", "publisher": "", "place": "", "date": "March 2008", "volume": "1", "issue": "1", "section": "", "partNumber": "", "partTitle": "", "pages": "34-41", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1109/JSTARS.2008.2001431", "citationKey": "", "url": "", "accessDate": "", "PMID": "", "PMCID": "", "ISSN": "1939-1404", "archive": "", "archiveLocation": "", "shortTitle": "Geographic Aspects of Photovoltaics in Europe", "language": "", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Data analysis", "type": 1 }, { "tag": "Europe", "type": 1 }, { "tag": "Feedback", "type": 1 }, { "tag": "Meteorology", "type": 1 }, { "tag": "PVGIS Website", "type": 1 }, { "tag": "Photovoltaic cells", "type": 1 }, { "tag": "Solar radiation", "type": 1 }, { "tag": "Spatial databases", "type": 1 }, { "tag": "Uncertainty", "type": 1 }, { "tag": "Web services", "type": 1 }, { "tag": "Yield estimation", "type": 1 }, { "tag": "atmospheric techniques", "type": 1 }, { "tag": "climate data", "type": 1 }, { "tag": "geo-simulation models", "type": 1 }, { "tag": "geodatabases", "type": 1 }, { "tag": "geographic information systems", "type": 1 }, { "tag": "geophysics computing", "type": 1 }, { "tag": "information networks", "type": 1 }, { "tag": "interactive maps", "type": 1 }, { "tag": "internet", "type": 1 }, { "tag": "knowledge distribution systems", "type": 1 }, { "tag": "photovolatic yield predictions", "type": 1 }, { "tag": "photovoltaic geographic aspects", "type": 1 }, { "tag": "photovoltaic geographic information system", "type": 1 }, { "tag": "photovoltaic power systems", "type": 1 }, { "tag": "photovoltaic technology performance assessment", "type": 1 }, { "tag": "solar energy projects", "type": 1 }, { "tag": "solar power stations", "type": 1 }, { "tag": "solar radiation estimate uncertainty", "type": 1 }, { "tag": "sunlight", "type": 1 }, { "tag": "temperature", "type": 1 }, { "tag": "web based knowledge distribution system", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2015-04-28T16:50:17Z", "dateModified": "2015-04-28T16:50:17Z" } } ]