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Physical Sciences and Mathematics Commons™
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Articles 1 - 7 of 7
Full-Text Articles in Physical Sciences and Mathematics
Determining And Evaluating New Store Locations Using Remote Sensing Andmachine Learning, Berkan Höke, Zeynep Zerri̇n Turgay, Cem Ünsalan, Hande Küçükaydin
Determining And Evaluating New Store Locations Using Remote Sensing Andmachine Learning, Berkan Höke, Zeynep Zerri̇n Turgay, Cem Ünsalan, Hande Küçükaydin
Turkish Journal of Electrical Engineering and Computer Sciences
Decision making for store locations is crucial for retail companies as the profit depends on the location. The key point for correct store location is profit approximation, which is highly dependent on population of the corresponding region, and hence, the volume of the residential area. Thus, estimating building volumes provides insight about the revenue if a new store is about to be opened there. Remote sensing through stereo/tri-stereo satellite images provides wide area coverage as well as adequate resolution for three dimensional reconstruction for volume estimation. We reconstruct 3D map of corresponding region with the help of semiglobal matching and …
A New Semiempirical Model Determining The Dielectric Characteristics Of Citrusleaves For The Remote Sensing At C Band, Abdullah Genç, Habi̇b Doğan, İbrahi̇m Bahadir Başyi̇ği̇t
A New Semiempirical Model Determining The Dielectric Characteristics Of Citrusleaves For The Remote Sensing At C Band, Abdullah Genç, Habi̇b Doğan, İbrahi̇m Bahadir Başyi̇ği̇t
Turkish Journal of Electrical Engineering and Computer Sciences
Dielectric parameters (i.e. permittivity) are fundamental to the simulation, design, modeling, and developing of microwave applications. For targeted objects, the complex permittivity is an essential parameter that affects its characteristics of scattering and microwave radiation. Thus, in microwave remote sensing applications, the knowledge of the dielectric property of vegetable materials is used not only to detect planting areas for monitoring and to able to specify the growth stage of them in seasonal variations, but also to determine the water requirement of the plant for controlling (water stress). This paper focuses on determining the dielectric parameters of orange and lemon leaves, …
A Multiseed-Based Svm Classification Technique For Training Sample Reduction, Imran Sharif, Debasis Chaudhuri
A Multiseed-Based Svm Classification Technique For Training Sample Reduction, Imran Sharif, Debasis Chaudhuri
Turkish Journal of Electrical Engineering and Computer Sciences
A support vector machine (SVM) is not a popular method for a very large dataset classification because the training and testing time for such data are computationally expensive. Many researchers try to reduce the training time of SVMs by applying sample reduction methods. Many methods reduced the training samples by using a clustering technique. To reduce its high computational complexity, several data reduction methods were proposed in previous studies. However, such methods are not effective to extract informative patterns. This paper demonstrates a new supervised classification method, multiseed-based SVM (MSB-SVM), which is particularly intended to deal with very large datasets …
Sar Image Time-Series Analysis Framework Using Morphological Operators And Global And Local Information-Based Linear Discriminant Analysis, Ufuk Sakarya, Caner Demi̇rpolat
Sar Image Time-Series Analysis Framework Using Morphological Operators And Global And Local Information-Based Linear Discriminant Analysis, Ufuk Sakarya, Caner Demi̇rpolat
Turkish Journal of Electrical Engineering and Computer Sciences
Fusion of spectral, spatial, and temporal information is an effective method used in many satellite remote sensing applications. On the other hand, one drawback of this fusion is an increase in complexity. In this paper, we focus on developing a fast and well-performed classification method for agricultural crops using time-series SAR data. In order to achieve this, a novel two-stage approach is proposed. In the first stage, a high-dimensional feature space is obtained using time-series dual-pol SAR data and morphological operators. Spectral, spatial, and temporal information is combined into a single high-dimensional feature space. In the second stage, a dimension …
Design And Implementation Of A Man-Overboard Emergency Discovery System Based On Wireless Sensor Networks, Abdullah Sevi̇n, Cüneyt Bayilmiş, İsmai̇l Ertürk, Hüseyi̇n Eki̇z, Ahmet Karaca
Design And Implementation Of A Man-Overboard Emergency Discovery System Based On Wireless Sensor Networks, Abdullah Sevi̇n, Cüneyt Bayilmiş, İsmai̇l Ertürk, Hüseyi̇n Eki̇z, Ahmet Karaca
Turkish Journal of Electrical Engineering and Computer Sciences
Recently, wireless sensor networks (WSNs) have been widely employed in many different fields such as military, surveillance, health, agricultural, automation, and environmental monitoring. This paper presents a designed and implemented WSN-based man-overboard emergency discovery system, abbreviated as W-MEDS, that discovers the location of a person in emergency circumstances and runs an alarm system on a ship. The developed W-MEDS carries out a fast man-overboard (MOB) discovery and initiates the vital rescue procedure. It mainly consists of a WSN and a control and discovery system. When a MOB accident occurs, this situation is easily detected through the WSN nodes capable of …
Integration Of Spectral And Spatial Information Via Local Covariance Matrices For Segmentation And Classification Of Hyperspectral Images, Uğur Ergül, Gökhan Bi̇lgi̇n
Integration Of Spectral And Spatial Information Via Local Covariance Matrices For Segmentation And Classification Of Hyperspectral Images, Uğur Ergül, Gökhan Bi̇lgi̇n
Turkish Journal of Electrical Engineering and Computer Sciences
In this work, a novel approach is presented for the feature extraction step in hyperspectral image processing to form more discriminative features between different pixel regions. The proposed method combines both spatial and spectral information, which is very important for segmentation and classification of hyperspectral images. For comparison, five different feature sets are formed using eigen decomposition of local covariance matrices of subcubes located around a pixel of interest in the scene. Subcubes of neighbor pixels are obtained by a windowed structure to expose pattern similarities. As a novel approach, local covariance matrices are computed in eigenspace and proposed feature …
Change Detection Without Difference Image Computation Based On Multiobjective Cost Function Optimization, Turgay Çeli̇k, Zeki̇ Yetgi̇n
Change Detection Without Difference Image Computation Based On Multiobjective Cost Function Optimization, Turgay Çeli̇k, Zeki̇ Yetgi̇n
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we propose a novel method for unsupervised change detection in multi-temporal satellite images by using multiobjective cost function optimization via genetic algorithm (GA). The spatial image grid of the input multi-temporal satellite images is divided into two distinct regions, representing ``changed'' and ``unchanged'' regions between input images, via the intermediate change detection mask produced by the GA. The dissimilarity of pixels of ``changed'' regions and similarity of pixels of ``unchanged'' regions between input multi-temporal images are measured using image quality metrics which consider correlation, spectral distortion, radiometric distortion, and contrast distortion. The contextual information of each pixel …