Now showing items 1-20 of 33

    • Autofocused spotlight SAR image reconstruction of off-grid sparse scenes 

      Camlıca, S.; Gurbuz, A. C.; Arıkan, Orhan (Institute of Electrical and Electronics Engineers Inc., 2017)
      Synthetic aperture radar (SAR) has significant role in remote sensing. Phase errors due to uncompensated platform motion, measurement model mismatch, and measurement noise can cause degradations in SAR image reconstruction. ...
    • Automatic detection of compound structures by joint selection of region groups from a hierarchical segmentation 

      Akçay, H. G.; Aksoy, S. (Institute of Electrical and Electronics Engineers, 2016)
      A challenging problem in remote sensing image analysis is the detection of heterogeneous compound structures such as different types of residential, industrial, and agricultural areas that are composed of spatial arrangements ...
    • Automatic detection of geospatial objects using multiple hierarchical segmentations 

      Akçay, H. G.; Aksoy, S. (Institute of Electrical and Electronics Engineers, 2008-07)
      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 ...
    • Building detection using directional spatial constraints 

      Akçay, H. Gökhan; Aksoy, Selim (IEEE, 2010)
      We propose an algorithm for automatic detection of buildings with complex shapes and roof structures in very high spatial resolution remotely sensed images. First, an initial oversegmentation is obtained. Then, candidate ...
    • Detection of compound structures using hierarchical clustering of statistical and structural features 

      Akçay, H. Gokhan; Aksoy, Selim (IEEE, 2011)
      We describe a new procedure that combines statistical and structural characteristics of simple primitive objects to discover compound structures in images. The statistical information that is modeled using spectral, shape, ...
    • Detection of compound structures using multiple hierarchical segmentations 

      Akçay, H. Gökhan; Aksoy, Selim (IEEE, 2012)
      In this paper, our aim is to discover compound structures comprised of regions obtained from hierarchical segmentations of multiple spectral bands. A region adjacency graph is constructed by representing regions as vertices ...
    • Finding compound structures in images using image segmentation and graph-based knowledge discovery 

      Zamalieva, Daniya; Aksoy, Selim; Tilton J. C. (IEEE, 2009-07)
      We present an unsupervised method for discovering compound image structures that are comprised of simpler primitive objects. An initial segmentation step produces image regions with homogeneous spectral content. Then, the ...
    • Fire detection and 3D fire propagation estimation for the protection of cultural heritage areas 

      Dimitropoulos, K.; Köse, Kıvanç; Grammalidis, N.; Çetin, A. Enis (Copernicus GmbH, 2010)
      Beyond taking precautionary measures to avoid a forest fire, early warning and immediate response to a fire breakout are the only ways to avoid great losses and environmental and cultural heritage damages. To this end, ...
    • Identification of materials with magnetic characteristics by neural networks 

      Nazlibilek, S.; Ege, Y.; Kalender O.; Sensoy, M.G.; Karacor, D.; Sazli, M.H. (2012)
      In industry, there is a need for remote sensing and autonomous method for the identification of the ferromagnetic materials used. The system is desired to have the characteristics of improved accuracy and low power ...
    • Image information mining using spatial relationship constraints 

      Karakuş, Fatih (Bilkent University, 2012)
      There is a huge amount of data which is collected from the Earth observation satellites and they are continuously sending data to Earth receiving stations day by day. Therefore, mining of those data becomes more important ...
    • Interactive training of advanced classifiers for mining remote sensing image archives 

      Aksoy, Selim; Koperski, K.; Tusk, C.; Marchisio G. (ACM, 2004)
      Advances in satellite technology and availability of down-loaded images constantly increase the sizes of remote sensing image archives. Automatic content extraction, classification and content-based retrieval have become ...
    • Ionogram scaling using Hidden Markov Models 

      Gök, Gökhan; Alp, Y. K.; Arıkan, Orhan; Arikan, F. (Institute of Electrical and Electronics Engineers, 2018)
      In this paper, a novel method for electron density reconstruction using ionosonde data is proposed. Proposed technique uses Hidden Markov Models for extracting echoes that provides valuable information about electron density ...
    • Ionolab grubunun iyonküre uzaktan algılama ve 2-b görüntüleme çalışmaları 

      Arıkan, F.; Toker, C.; Sezen, U.; Deviren, M. N.; Çilibaş, O.; Arıkan, Orhan (IEEE, 2014-04)
      Bu çalışmada, IONOLAB grubunun son 10 yıldır iyonküre uzaktan algılaması ve 2-B görüntüleme çalışmaları özetlenecektir. TÜBİTAK EEEAG 105E171 ve 109E055 projelerinde, çift frekanslı Yerküresel Konumlama Sistemi (YKS) ...
    • Kentsel yapıların biçimbilimsel bölütlenmesi 

      Akçay, H. Gökhan; Aksoy, Selim (IEEE, 2007-06)
      Yüksek çözünürlükteki uzaktan algılamalı uydu görüntülerinde bölütleme kent uygulamalarında önemli bir problemdir çünkü elde edilen bölütlemelerle sınıflandırma için piksel tabanlı spektral bilginin yanında uzamsal ve ...
    • Land cover classification with multi-sensor fusion of partly missing data 

      Aksoy, S.; Koperski, K.; Tusk, C.; Marchisio, G. (American Society for Photogrammetry and Remote Sensing, 2009-05)
      We describe a system that uses decision tree-based tools for seamless acquisition of knowledge for classification of remotely sensed imagery. We concentrate on three important problems in this process: information fusion, ...
    • Learning bayesian classifiers for scene classification with a visual grammar 

      Aksoy, Selim; Koperski, K.; Tusk, C.; Marchisio, G.; Tilton J. C. (IEEE, 2005)
      A challenging problem in image content extraction and classification is building a system that automatically learns high-level semantic interpretations of images. We describe a Bayesian framework for a visual grammar that ...
    • Learning bayesian classifiers for scene classification with a visual grammar 

      Aksoy, Selim; Koperski, K.; Tusk, C.; Marchisio, G.; Tilton, J. C. (IEEE, 2005-03)
      A challenging problem in image content extraction and classification is building a system that automatically learns high-level semantic interpretations of images. We describe a Bayesian framework for a visual grammar that ...
    • Metamaterial-based wireless RF-MEMS strain sensors 

      Melik, Rohat; Ünal, Emre; Perkgoz, Nihan Kosku; Puttlitz, C.; Demir, Hilmi Volkan (IEEE, 2010)
      Approximately 10% of the fractures do not heal properly because of the inability to monitor fracture healing. Standard radiography is not capable of discriminating whether bone healing is occurring normally or aberrantly. ...
    • Mining of remote sensing image archives using spatial relationship histograms 

      Kalaycılar, Fırat; Kale, Aslı; Zamalieva, Daniya; Aksoy, Selim (IEEE, 2008-07)
      We describe a new image representation using spatial relationship histograms that extend our earlier work on modeling image content using attributed relational graphs. These histograms are constructed by classifying the ...
    • Modeling of remote sensing image content using attributed relational graphs 

      Aksoy, Selim (Springer, 2006-08)
      Automatic content modeling and retrieval in remote sensing image databases are important and challenging problems. Statistical pattern recognition and computer vision algorithms concentrate on feature-based analysis and ...