Relevant bibliographies by topics / ERDAS IMAGINE

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'ERDAS IMAGINE'

Author: Grafiati
Published: 4 June 2021
Last updated: 26 July 2025

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Journal articles on the topic "ERDAS IMAGINE"

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Reshetilo, Natalya S., and Elena P. Khlebnikova. "POSSIBILITY OF USING REMOTE SENSING DATA FOR MONITORING WATER OBJECTS." Interexpo GEO-Siberia 6 (May 21, 2021): 248–55. http://dx.doi.org/10.33764/2618-981x-2021-6-248-255.

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The article discusses the use of Earth remote sensing methods. The analysis and mapping of changes in the boundaries of the Iyariver in the city of Tulun, Irkutsk region, was carried out using the Erdas Imagine 2015 software package.
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Баланбаев, Даулет. "Особеннось дешифрирования пространственных объектов по космическим снимкам в программе “ЕRDAS IMAGINIE”". Рroblems of engineering and professional education 42, № 3 (2023): 41–48. http://dx.doi.org/10.32523/2220-685x-2017-42-3-41-48.

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В данной статье рассматриваются общее понятие дешифрирования космических снимков и его особенности в современном мире; некоторые способы использования автоматической (кластерной) и контролируемой (с обучением) классификаций, которые заложены в программе Erdas Imagine. На отдельных примерах анализируются результаты дешифрирования пространственных объектов
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Dobesova, Zdena. "Cognition of Graphical Notation for Processing Data in ERDAS IMAGINE." ISPRS International Journal of Geo-Information 10, no. 7 (2021): 486. http://dx.doi.org/10.3390/ijgi10070486.

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This article presents an evaluation of the ERDAS IMAGINE Spatial Model Editor from the perspective of effective cognition. Workflow models designed in Spatial Model Editor are used for the automatic processing of remote sensing data. The process steps are designed as a chain of operations in the workflow model. The functionalities of the Spatial Model Editor and the visual vocabulary are both important for users. The cognitive quality of the visual vocabulary increases the comprehension of workflows during creation and utilization. The visual vocabulary influences the user’s exploitation of wo
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Nelson, Stacy A. C., Siamak Khorram, and Shiloh Dorgan. "Image Processing and Data Analysis with ERDAS IMAGINE." Photogrammetric Engineering & Remote Sensing 86, no. 10 (2020): 597–98. http://dx.doi.org/10.14358/pers.86.10.597.

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Chen, Hao, Tian Liang, and Juan Yao. "The Processing Algorithms and EML Modeling of True Color Synthesis for SPOT5 Image." Applied Mechanics and Materials 373-375 (August 2013): 564–68. http://dx.doi.org/10.4028/www.scientific.net/amm.373-375.564.

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SPOT-5 image is widely used in every trade by its special advantage of high spatial resolution and stereo mapping. SPOT-5 image is difficult to composite true color without blue wavelength channel. This article aims to achieve approximation from RS images colors to natural colors through true-color processing. The experiential arithmetic module of true-color composite is established by Using Erdas Imagine, which is the software for processing RS image, and ERDAS Macro Language (EML), which is modeling language. Loading module and some simulations get more effective images of approximating natu
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Sun, Tong He, and Guo Qing Yan. "Land Utilization and Classification Method Based on Remote Sensing Technology." Applied Mechanics and Materials 239-240 (December 2012): 501–6. http://dx.doi.org/10.4028/www.scientific.net/amm.239-240.501.

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This paper discusses land utilization classification based on remote sensing technology. Taking the Xinjiang Kulja county bureau department area remote sensing images as the basic information, and using ERDAS IMAGINE, this paper discusses non-supervised classification and supervised classification methods. The results show that remote sensing technology applies to land utilization situation and land classification, which has reference value.
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Plotnikova, Marina, and Elena Khlebnikova. "MONITORING OF URBAN AREA WITH SATELLITE IMAGERY." Interexpo GEO-Siberia 6, no. 1 (2019): 86–93. http://dx.doi.org/10.33764/2618-981x-2019-6-1-86-93.

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The problem of identifying changes occurring in the territory of an urban area due to construction of new facilities, renovations and reconstructions using remote sensing of the Earth was considered. Various algorithms for automated detection of changes from different-time satellite images in the ERDAS IMAGINE 2010 program are analyzed in practice. Factors that must be considered when monitoring urban areas are identified.
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Zeng, Guang Wei, Gui Fen Chen, Chu Nan Li, and Jiao Ye. "The Comparative Study of Remote Sensing Image Classification Method Based on ERDAS." Advanced Materials Research 546-547 (July 2012): 542–47. http://dx.doi.org/10.4028/www.scientific.net/amr.546-547.542.

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ERDAS IMAGINE is a remote sensing image processing system developed by the United States.The paper using ERDAS to classified the remote sensing of Land-sat TM image data by supervised classification method and unsupervised classification method, Using the Yushu City remote sensing image of Jilin Province as the trial data, and classified the forest, arable land and water from the remote sensing images, compared the test data of the supervised classification and unsupervised classification method, shows that the supervised classification method can be better to solute the questions "with the sp
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Kaimaris, Dimitris, Petros Patias, and Maria Sifnaiou. "UAV and the comparison of image processing software." International Journal of Intelligent Unmanned Systems 5, no. 1 (2017): 18–27. http://dx.doi.org/10.1108/ijius-12-2016-0009.

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Purpose The purpose of this paper is to discuss unmanned aerial vehicle (UAV) and the comparison of image processing software. Design/methodology/approach Images from a drone are used and processed with new digital image processing software, Imagine UAV® of Erdas imagine 2015®. The products (Digital Surface Model and ortho images) are validated with check points (CPs) measured in the field with Global Positioning System. Moreover, similar products are produced by Agisoft PhotoScan® software and are compared with both the products of Imagine UAV and the CPs. Findings The results reveal that the
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Pal, Shreesty, S. K. Pandey, S. K. Sharma, and Reena Nair. "Acreage estimation of mango orchards in Jabalpur district of Madhya Pradesh using Sentinel-2 imagery." Ecology, Environment and Conservation 29, no. 02 (2023): 840–44. http://dx.doi.org/10.53550/eec.2023.v29i02.050.

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An approach was made to evaluate the area and perform spatial mapping of mango orchards using satellite image obtained from Sentinel-2 for Jabalpur district of Madhya Pradesh. The image was processed using ERDAS IMAGINE software. Supervised classification was performed for acreage estimation. An area of 1217 ha was found to be occupied by mango orchards, covering 0.24% of total area of Jabalpur district. The study has distinctly exhibited the adequacy of remote sensing imagery for identification and area estimation of mango orchards.
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Dissertations / Theses on the topic "ERDAS IMAGINE"

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Marques, Junior Luiz Carlos. "Classificação de plantas daninhas em banco de imagens utilizando redes neurais convolucionais /." Bauru, 2019. http://hdl.handle.net/11449/182521.

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Orientador: José Alfredo Covolan Ulson<br>Banca: Adriano de Souza Marques<br>Banca: Fernando de Souza Campos<br>Resumo: As espécies exóticas invasoras, também conhecidas como plantas daninhas, competem por recursos, como sol, água e nutrientes paralelamente a cultura plantada, impondo prejuízos econômicos ao agricultor. Para minimizar este problema, atualmente os agricultores fazem uso de herbicidas para a eliminação e/ou controle das plantas daninhas. O uso de herbicidas depara-se com problemas: i) algumas plantas daninhas são resistentes a aplicação de herbicidas e, ii) quando aplicados em d
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Davis, Tiana. "Quantifying Chlorophyll a Content Through Remote Sensing: A Pilot Study of Utah Lake." Diss., CLICK HERE for online access, 2006. http://contentdm.lib.byu.edu/ETD/image/etd1261.pdf.

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Coltri, Mariana Bianchini Malerba. "Imagens de herbários do século XVI como formas de registro e comunicação de conhecimentos: O herbário de William Turner (c.1510 - 1568)." Pontifícia Universidade Católica de São Paulo, 2017. https://tede2.pucsp.br/handle/handle/20081.

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Submitted by Filipe dos Santos (fsantos@pucsp.br) on 2017-05-12T13:15:39Z No. of bitstreams: 1 Mariana Bianchini Malerba Coltri.pdf: 44585552 bytes, checksum: 28da7fc5db4f7d22c0537decd3588adf (MD5)<br>Made available in DSpace on 2017-05-12T13:15:39Z (GMT). No. of bitstreams: 1 Mariana Bianchini Malerba Coltri.pdf: 44585552 bytes, checksum: 28da7fc5db4f7d22c0537decd3588adf (MD5) Previous issue date: 2017-03-08<br>Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES<br>In this study, we analyze the relevance of the images in herbaria from the XVIth century, emphasizing main
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KOTLABOVÁ, Soňa. "Vyhotovení stručného návodu pro software Leica ERDAS IMAGINE v 9.1 s přihlédnutím jeho aplikace pro potřeby výuky KPÚ." Master's thesis, 2011. http://www.nusl.cz/ntk/nusl-48273.

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The aim of this work is to get familiar with the environment and data processing in the program ERDAS IMAGINE and then based on acquired knowledge to prepare a brief tutorial that will be usable for teaching.The first part deals with remote sensing (RS), its methods, output data and data gathering. The second part is the instruction. The instruction containes of essential features of the program, such as settings, description of the menu, creation and adjustment of data and data output. The work contains a large amount of image data.
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PINKAVOVÁ, Šárka. "Využití metod a dat DPZ při tvorbě KPÚ." Master's thesis, 2008. http://www.nusl.cz/ntk/nusl-44845.

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This diploma thesis covers questions of remote sensing in relation to land adjustment. On water area is showm usage of the vegetation index NDVI and the Tasseled Cap transformation. Satellite images were processed in computer software ERDAS IMAGINE.
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JURÁNEK, Stanislav. "Tvorba digitálního modelu terénu pro povodí Jenínského toku a analýza drah soustředěného odtoku vod." Master's thesis, 2008. http://www.nusl.cz/ntk/nusl-44840.

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The aim of the thesis is localization and interpretation of paths of concentration runoff in digital terrain model. Digital terrain model(DTM) is processed for the catchment of the Jenín stream, where The Faculty of Agriculture has held the research since the year 2004. For creation of DTM following software programs were used for comparison: Erdas and ArcGIS. Digitalized maps of contour lines for this catchment were the backgrounds for creation of the DTM. Localization of paths of concentration runoff and natural thalwegs was made on created DTM. Then was the comparison of models and the real
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Nephawe, Mbavhalelo. "An assessment of the impacts of land use changes on the Duthuni wetland stream using remote sensing, GIS and social surveying: a case study in Limpopo Province, South Africa." Diss., 2017. http://hdl.handle.net/11602/892.

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MENVSC<br>Department of Geography and Geo-Information Sciences<br>This is a case study research that focuses on the assessment of the impacts of land use changes on the Duthuni wetland ecosystem in Limpopo Province using geospatial techniques and Social Survey. SPOT 4 satellite images which covered the time frame between 1999, 2005 to 2012, were used. The unit of analysis included different institutions such as the local municipality, farmers, the heads of the households and Chief of the Village. In this study, different methods of sampling were used in different context for selecting particip
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Books on the topic "ERDAS IMAGINE"

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(Firm), ERDAS, ed. ERDAS IMAGINE tour guides. ERDAS Inc., 1997.

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Nelson, Stacy A. C., and Siamak Khorram. Image Processing and Data Analysis with ERDAS IMAGINE®. CRC Press, 2018. http://dx.doi.org/10.1201/b21969.

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Geological Survey (U.S.). National Mapping Division, ed. Enhancing USGS image processing capabilities: The development of a users guide, video tape guide, and in-house course outline for ERDAS software. U.S. Dept. of the Interior, U.S. Geological Survey, National Mapping Division, 1994.

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Image Processing and Data Analysis with ERDAS IMAGINE®. Taylor & Francis Group, 2018.

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Khorram, Siamak, and Stacy A. C. Nelson. Image Processing and Data Analysis with ERDAS IMAGINE®. Taylor & Francis Group, 2018.

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Khorram, Siamak, and Stacy A. C. Nelson. Image Processing and Data Analysis with ERDAS IMAGINE®. Taylor & Francis Group, 2018.

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Khorram, Siamak, and Stacy A. C. Nelson. Image Processing and Data Analysis with ERDAS IMAGINE®. Taylor & Francis Group, 2018.

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Khorram, Siamak, and Stacy A. C. Nelson. Image Processing and Data Analysis with ERDAS IMAGINE®. Taylor & Francis Group, 2018.

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Schwyzer, Philip. Nationalism in the Renaissance. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780199935338.013.70.

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Although an influential school of thought locates the origins of nationalism in the late eighteenth century, the Tudor era has long been associated with the rise of English national consciousness. This chapter surveys recent studies of sixteenth-century nationalism and argues that the national community imagined in Tudor literature was in many respects more British than English. Whether or not a developed nationalist ideology was present in sixteenth-century England, the works of Shakespeare and his contemporaries have been crucial to the development and expression of national consciousness in
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Briesacher, Erika L. Festival, Culture, and Identity in Lübeck. The Rowman & Littlefield Publishing Group, 2022. https://doi.org/10.5040/9781666992076.

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In this study Erika L. Briesacher argues that festivals in Lübeck, Germany spanning 1920 to 1960 demonstrate interlocking economic, social, and cultural factors that contribute to local, national, and international identity formation. Focusing on institutional records as well as public discourse and material artifacts, the author traces the mobilization of “Nordic” as a distinctly German in-group during the Weimar, Nazi, and early Cold War eras, highlighting particular ways participants included and excluded racial, religious, and other cultural identities in their own “imagined community.” Fo
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Book chapters on the topic "ERDAS IMAGINE"

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Nelson, Stacy A. C., and Siamak Khorram. "Acquiring Data: EarthExplorer, GloVis, LandsatLook Viewer, and NRCS Geospatial Data Gateway." In Image Processing and Data Analysis with ERDAS IMAGINE®. CRC Press, 2018. http://dx.doi.org/10.1201/b21969-1.

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Nelson, Stacy A. C., and Siamak Khorram. "Supervised Classification." In Image Processing and Data Analysis with ERDAS IMAGINE®. CRC Press, 2018. http://dx.doi.org/10.1201/b21969-10.

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Nelson, Stacy A. C., and Siamak Khorram. "Object Based Image Analysis." In Image Processing and Data Analysis with ERDAS IMAGINE®. CRC Press, 2018. http://dx.doi.org/10.1201/b21969-11.

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Nelson, Stacy A. C., and Siamak Khorram. "Additional Image Analysis Techniques." In Image Processing and Data Analysis with ERDAS IMAGINE®. CRC Press, 2018. http://dx.doi.org/10.1201/b21969-12.

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Nelson, Stacy A. C., and Siamak Khorram. "Assessing Thematic Classification Accuracy." In Image Processing and Data Analysis with ERDAS IMAGINE®. CRC Press, 2018. http://dx.doi.org/10.1201/b21969-13.

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Nelson, Stacy A. C., and Siamak Khorram. "Basics of Digital Stereoscopy." In Image Processing and Data Analysis with ERDAS IMAGINE®. CRC Press, 2018. http://dx.doi.org/10.1201/b21969-14.

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Nelson, Stacy A. C., and Siamak Khorram. "Introduction to Image Data Processing." In Image Processing and Data Analysis with ERDAS IMAGINE®. CRC Press, 2018. http://dx.doi.org/10.1201/b21969-2.

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Nelson, Stacy A. C., and Siamak Khorram. "Georectification." In Image Processing and Data Analysis with ERDAS IMAGINE®. CRC Press, 2018. http://dx.doi.org/10.1201/b21969-3.

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Nelson, Stacy A. C., and Siamak Khorram. "Orthorectification." In Image Processing and Data Analysis with ERDAS IMAGINE®. CRC Press, 2018. http://dx.doi.org/10.1201/b21969-4.

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Nelson, Stacy A. C., and Siamak Khorram. "Positional Accuracy Assessment." In Image Processing and Data Analysis with ERDAS IMAGINE®. CRC Press, 2018. http://dx.doi.org/10.1201/b21969-5.

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Conference papers on the topic "ERDAS IMAGINE"

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Nwaogu, Chukwudi, Babatunde Alabi, Nasir A. Uma, Bridget E. Diag, Victor A. Agidi, and Chinwe G. Onwuagb. "LAND USE-COVER CHANGE TRAJECTORY AND IMPLICATION ON THE AGRICULTURAL AREAS OF SAO PAULO CITY: A GEOINFORMATICS APPROACH." In 24th SGEM International Multidisciplinary Scientific GeoConference 2024. STEF92 Technology, 2024. https://doi.org/10.5593/sgem2024/2.1/s08.17.

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Agricultural productivity and environmental changes can be greatly affected by agricultural and other land use. Mapping of vegetation and land cover is a fundamental way of managing the natural resources on the earth surface. To determine or study the crop productivities of any geographical location, agricultural land use is one of the crucial clues for reliable information. We aimed to investigate the effects of urbanization on agricultural lands in Sao Paulo city. A 30-year multi-temporal satellite imagery dataset from four distinct years were mapped: 1992 (Landsat TM), 2002 (Landsat ETM+),
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Khawas, Chunnu, Mohan P. Pradhan, Ratika Pradhan, and Ashis Pradhan. "Landsat8-9 Satellite Image Classification with ERDAS for Mapping the Urban Spaces of East Sikkim." In 2025 3rd International Conference on Intelligent Systems, Advanced Computing and Communication (ISACC). IEEE, 2025. https://doi.org/10.1109/isacc65211.2025.10969356.

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Решетило, Наталья Сергеевна, та Елена Павловна Хлебникова. "Возможность использования данных дистанционного зондирования при мониторинге водных объектов". У Регулирование земельно-имущественных отношений в России: правовое и геопространственное обеспечение, оценка недвижимости, экология, технологические решения - 2021-3. СГУГиТ, 2021. http://dx.doi.org/10.33764/2687-041x-2021-3-73-81.

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В статье рассмотрены первостепенные задачи мониторинга водных объектов, цели, возможности использования данных дистанционного зондирования с применением программного комплекса Erdas Imagine 2015. Показано как с помощью данных дистанционного зондирования можно получить достоверную информацию о состоянии водных объектов, выявить и спрогнозировать неблагоприятные экологические явления, а также извлечь полезную информацию.
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Плотникова, Марина Александровна, та Елена Павловна Хлебникова. "Возможности применения космических снимков высокого разрешения при мониторинге городских территорий". У Регулирование земельно-имущественных отношений в России: правовое и геопространственное обеспечение, оценка недвижимости, экология, технологические решения - 2021-3. СГУГиТ, 2021. http://dx.doi.org/10.33764/2687-041x-2021-3-55-60.

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В статье рассмотрены особенности выявления изменений, происходящих на территории городского пространства в связи со строительством новых объектов, с помощью архивных спутниковых снимков высокого разрешения Sentinel-2. Применен алгоритм автоматизированного выявления изменений, основанный на использовании индексных изображений в программе ERDAS IMAGINE 2010. Выявлены дальнейшие перспективы мониторинга городских территорий по космическим снимкам.
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Auer, Stefan, Daniele Cerra, Peter Gege, et al. "Reconnaissance of coastal areas using simulated EnMAP data in an ERDAS IMAGINE environment." In Earth Resources and Environmental Remote Sensing/GIS Applications, edited by Ulrich Michel and Karsten Schulz. SPIE, 2018. http://dx.doi.org/10.1117/12.2325402.

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Bispo, Vitória Maria S., Natália Fernanda de C. Meira, Ricardo A. R. Campos, and Andrea G. Campos Bianchi. "Explorando DCGANs na geração de imagens citológicas para diagnóstico assistido por computador." In Escola Regional de Computação Aplicada à Saúde. Sociedade Brasileira de Computação - SBC, 2024. http://dx.doi.org/10.5753/ercas.2024.238706.

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Na área de citologia, a precisão dos diagnósticos assistidos por computador depende do treinamento do modelo de inteligência artificial com um extenso conjunto de dados rotulados. Este trabalho propõe a utilização de Redes Generativas Adversárias Convolucionais Profundas (DCGANs) para gerar imagens artificiais para ampliar a quantidade e a diversidade das amostras citológicas para treinamento. Foram desenvolvidos dois modelos: uma DCGAN convencional e uma pré-treinada a partir dos parâmetros da primeira. Os resultados qualitativos sugerem que as imagens sintéticas produzidas são representativa
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Carvalho, Elisson C., Alessandra M. Coelho, and Matheus F. O. Baffa. "Detecção do Câncer de Mama em Imagens Infravermelhas Utilizando Características Radiômicas." In Escola Regional de Computação Aplicada à Saúde. Sociedade Brasileira de Computação - SBC, 2021. http://dx.doi.org/10.5753/ercas.2021.17433.

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O câncer de mama é o segundo tipo mais frequente de câncer no mundo. Quando diagnosticado precocemente, o paciente pode apresentar um melhor prognóstico e aumentar suas chances de cura. Neste trabalho é proposto o desenvolvimento de um método de classificação de imagens infravermelhas para o auxílio no diagnóstico do câncer de mama. Para isso, utilizou-se características baseadas em radiômicas para representar o conteúdo da imagem em conjunto com uma Rede Neural Profunda para detecção de padrões e construção do modelo de classificação. Avaliado seguindo o procolo de Validação Cruzada, o método
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Sabino, Alan U., Adriana V. Safatle-Ribeiro, Fauze Maluf-Filho, and Alexandre F. Ramos. "Motiro: a unified automatic framework for statistical analysis of probe-based confocal laser endomicroscopy videos of colorectal mucosa." In Escola Regional de Computação Aplicada à Saúde. Sociedade Brasileira de Computação - SBC, 2021. http://dx.doi.org/10.5753/ercas.2021.17432.

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Probe-based Confocal Laser Endomicrocopy (pCLE) enables imaging the colorectal mucosa for screening and surveillance of cancer. Analyzing acquired videos relies on subjectivity of the endomicroscopists. Quantitative criteria are needed to enhance the diagnostics obtained using pCLE. We present Motiro, an automatic framework to extract features of the colorectal mucosa imaged by pCLE. Morphometric features of the crypts of the healthy colorectal mucosa are analysed and their variability quantified using the Shannon entropy. Hellinger distance compares the statistics of a morphometric parameter
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G. Júnior, Ederson N. F., Guilherme S. M. C. Paes, and Pedro Silva. "Classificação de Tumor Cerebral utilizando Deep Learning." In Escola Regional de Computação Aplicada à Saúde. Sociedade Brasileira de Computação - SBC, 2024. http://dx.doi.org/10.5753/ercas.2024.238597.

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A classificação de tumores cerebrais é um desafio crucial no campo da medicina e que pode ser auxiliada pela computação. Este estudo busca aprimorar a identificação de tumores cerebrais por meio do uso de Convolutional Neural Network (CNN), especificamente a arquitetura EfficientNetB0. Utilizando imagens de ressonância magnética, realizou-se a identificação com uma acurácia de 99,33%.
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10

Rodrigues, Natália Caroline de Oliveira. "Experimento da utilização de Deep Learning para auxílio na detecção de Tumor Cerebral." In Escola Regional de Computação Aplicada à Saúde. Sociedade Brasileira de Computação - SBC, 2024. http://dx.doi.org/10.5753/ercas.2024.238716.

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Abstract:
O artigo demonstra o potencial de redes neurais, como EfficientNetB1, VGG-19 e VGG-16, na detecção e classificação de tumores cerebrais através de imagens de ressonância magnética. Destaca-se que o EfficientNetB1 superou os demais, ressaltando a relevância do aprendizado profundo na medicina e sua aplicabilidade em contextos educacionais para enriquecer o conhecimento e práticas médicas.
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