Computer vision system and method employing hierarchical object classification schemeUS7043075 2002年6月27日 2006年5月9日 Koninklijke Philips Electronics N.V. Computer vision system and method employing hierarchical object classification schemeUS7043075 * Jun 27, 2002 May 9, 2006 Koninklijke Philips ...
It cuts down on the probability assigned by the system of an object belonging to a specific class by some amount, thus resulting in a more stable model and accurate classification of objects. Here is a standardized overview of how YOLO works: The image is divided into a grid of 13*13 =...
But to achieve this an accurate classification of everything in the database (including QSOs galaxies and solar system objects) will be required as will a detailed determination of stellar parameters (effective temperatures radii metallicities etc.). I shall discuss various multidimensional data ...
His research interest is in computer vision for mobile robotics with emphasis on probabilistic algorithms for object classification applied to range images. Viet Nguyen is a Ph.D. student at the École Polytechnique Fédérale de Lausanne (EPFL). He received his Bachelor’s degree in software ...
Image classification is the most classical vision task and possesses countless solutions, but some drawbacks remain. Current studies rely heavily on an extensive dataset for training, even with weak adaptation capability on previously unseen novel classes, and overfitting frequently occurs in long-tailed...
Object detection overlaps with other computer vision techniques, but developers nevertheless treat it as a discrete endeavor. Image classification (or image recognition) aims to classify images according to defined categories. A rudimentary example of this is CAPTCHA image tests, in which a group of ...
Fine-grained object classification is a challenging task due to the subtle inter-class difference and large intra-class variation. Recently, visual attention models have been applied to automatically localize the discriminative regions of an image for better capturing critical difference and demonstrated ...
(i.e., which objects are associated with each other). One previous study examined multivoxel patterns for scenes and objects and found no relationship between contextually related objects in the PPA36; however, this study only tested eight object categories and used simple pattern classification ...
classification via a naive Bayes classifier with online update in the compressed domain. A coarse-to-fine search strategy is adopted to further reduce the computational complexity in the detection procedure. The proposed compressive tracking algorithm runs in real-time and performs favorably against ...
3. We design a metric-based object classification method to classify objects into sub-classes and detect objects that do not appear in the training phase, in other words, untrained objects. The remainder of this manuscript is structured as follows. Section 2 introduces some related works of obje...