Browsing by Keywords "Object detection"
Now showing items 1-19 of 19
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Automatic detection of compound structures by joint selection of region groups from a hierarchical segmentation
(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 compound structures by joint selection of region groups from multiple hierarchical segmentations
(Bilkent University, 2016-09)A challenging problem in remote sensing image interpretation is the detection of heterogeneous compound structures such as different types of residential, industrial, and agricultural areas that are comprised of spatial ... -
Automatic detection of geospatial objects using multiple hierarchical segmentations
(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 ... -
Bağlamsal çıkarımla nesne sezimi
(IEEE, 2009-04)Bu bildiride, sezim başarımını arttırmada tek tek sezilmiş nesneler arasındaki bağlamsal ilişkilerden yararlanan bir nesne sezim sistemi tanıtılmaktadır. Bu çalışmadaki ilk katkı, iki boyutlu görüntü uzayında yapılan ... -
ConceptMap: mining noisy web data for concept learning
(Springer, 2014-09)We attack the problem of learning concepts automatically from noisy Web image search results. The idea is based on discovering common characteristics shared among subsets of images by posing a method that is able to organise ... -
Detection and classification of objects and texture
(Bilkent University, 2009)Object and texture recognition are two important subjects in computer vision. An efficient and fast algorithm to compute a short and efficient feature vector for classification of images is crucial for smart video ... -
Detection of compound structures by region group selection from hierarchical segmentations
(IEEE, 2016-07)Detection of compound structures that are comprised of different arrangements of simpler primitive objects has been a challenging problem as commonly used bag-of-words models are limited in capturing spatial information. ... -
Detection of compound structures using a gaussian mixture model with spectral and spatial constraints
(Institute of Electrical and Electronics Engineers Inc., 2014)Increasing spectral and spatial resolution of new-generation remotely sensed images necessitate the joint use of both types of information for detection and classification tasks. This paper describes a new approach for ... -
Detection of compound structures using hierarchical clustering of statistical and structural features
(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
(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 ... -
Detection of tree trunks as visual landmarks in outdoor environments
(Bilkent University, 2010)One of the basic problems to be addressed for a robot navigating in an outdoor environment is the tracking of its position and state. A fundamental first step in using algorithms for solving this problem, such as various ... -
Finding compound structures in images using image segmentation and graph-based knowledge discovery
(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
(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, ... -
Image mining using directional spatial constraints
(Institute of Electrical and Electronics Engineers, 2010-01)Spatial information plays a fundamental role in building high-level content models for supporting analysts' interpretations and automating geospatial intelligence. We describe a framework for modeling directional spatial ... -
Object detection using optical and LiDAR data fusion
(IEEE, 2016-07)Fusion of aerial optical and LiDAR data has been a popular problem in remote sensing as they carry complementary information for object detection. We describe a stratified method that involves separately thresholding the ... -
Object detection using optical and lidar data fusion with graph-cuts
(Bilkent University, 2017-03)Object detection in remotely sensed data has been a popular problem and is commonly used in a wide range of applications in domains such as agriculture, navigation, environmental management, urban monitoring and mapping. ... -
Performance measures for object detection evaluation
(Elsevier BV, 2010)We propose a new procedure for quantitative evaluation of object detection algorithms. The procedure consists of a matching stage for finding correspondences between reference and output objects, an accuracy score that is ... -
Unsupervised detection of compound structures using image segmentation and graph-based texture analysis
(Bilkent University, 2009)The common goal of object-based image analysis techniques in the literature is to partition the images into homogeneous regions and classify these regions. However, such homogeneous regions often correspond to very small ... -
Weakly supervised object localization with multi-fold multiple instance learning
(IEEE Computer Society, 2017)Object category localization is a challenging problem in computer vision. Standard supervised training requires bounding box annotations of object instances. This time-consuming annotation process is sidestepped in weakly ...
