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akaturk Academic measurement

OpenAlex topic

Remote-Sensing Image Classification

This page lists works and academicians tagged with an OpenAlex topic. It is not a YÖKSİS primary or secondary field.

OpenAlex 1,971 works 133 author topics

Works

1,971 works

  1. OpenAlex top 1% OpenAlex 99.9%

    No abstract yet.

  2. YÖKSİS SJR Q1 JCR Q1 OpenAlex top 1% OpenAlex 99.5%

    No abstract yet.

  3. YÖKSİS JCR Q2 OpenAlex top 1% OpenAlex 99.5%

    No abstract yet.

  4. OpenAlex top 1% OpenAlex 100.0%

    No abstract yet.

  5. YÖKSİS SJR Q2 JCR Q3 OpenAlex top 10% OpenAlex 96.4%

    No abstract yet.

  6. YÖKSİS SJR Q1 JCR Q1 OpenAlex top 10% OpenAlex 98.2%

    Artificial neural networks (ANNs) are used for land cover classification using remotely sensed data. Training of a neural network requires that the user specifies the network structure and sets the learning parameters. In this study, the optimum design of ANNs for classification problems is investigated. Heuristics pr…

  7. YÖKSİS SJR Q1 JCR Q1 OpenAlex top 1% OpenAlex 99.5%

    Very high resolution satellite images provide valuable information to researchers. Among these, urban-area boundaries and building locations play crucial roles. For a human expert, manually extracting this valuable information is tedious. One possible solution to extract this information is using automated techniques.…

  8. OpenAlex top 1% OpenAlex 99.7%

    No abstract yet.

  9. YÖKSİS SJR Q1 JCR Q2 OpenAlex top 10% OpenAlex 97.6%

    More than most European cities, Istanbul is experiencing considerable pressure from urban development due to a rapidly increasing population. As a consequence the land use activities in urban and suburban areas are changing dramatically. To provide cost-effective information about the current state and how it is chang…

  10. YÖKSİS SJR Q1 JCR Q1 OpenAlex top 1% OpenAlex 99.2%

    No abstract yet.

  11. OpenAlex top 1% OpenAlex 99.8%

    The object-based analysis of remotely sensed imagery provides valuable spatial and structural information that is complementary to pixel-based spectral information in classification. In this paper, we present novel methods for automatic object detection in high-resolution images by combining spectral information with…

  12. YÖKSİS SJR Q3 JCR Q3 OpenAlex top 10% OpenAlex 93.6%

    This study aims to examine the performance of Random Forest (RF) and Maximum Likelihood Classification (MLC) method to crop classification through pixel-based and parcel-based approaches. Analyses are performed on multispectral SPOT 5 image. First, the SPOT 5 image is classified using the classification methods in pix…

Academicians

133 academicians