An Evaluate of Pattern Identification Programs and Its Strategies

At the moment existence, Pattern Recognition has turned into an essential idea from analyst perspective. It is utilized as a part of numerous applications like Speech acknowledgment, facade acknowledgment, Biometrics and numerous other moreover. This survey paper will clarify numerous applications and methodologies of the example acknowledgment. Primarily four sorts of methodologies measurable, layout, auxiliary and neural approach. Furthermore, promote factual approach order is likewise done

Pengembangan Sistem Pengenalan Wajah Dengan Metode Pengklasifikasian Hibrid Berbasis Jaringan Fungsi Basis Radial Dan Pohon Keputusan Induktif

Face recognition is a difficult task mostly because of the inherent variability of the image formation process ranging from the position/cropping of the face and its environment (distance and illumination) is totally controlled, to those involving little or no control over the background and viewpoint. Moreover, those are allowing for major changes in facial appearance due to factors expression, aging, and accessories such as glasses or changes in hairstyle. A solution has been proposed by considering hybrid classification architectures deal with the benefit of robustness via consensus provided by ensembles of Radial Basis Functions (RBF) networks and categorical classification using decision trees. A specific approach considers an ensemble of RBF Networks through its ability to cope with variability in the image formation. The experiments were carried out on images drawn randomly 50 unique subjects totalling to 500 facial images with rotation ± 50 encoded in greyscale. The faces are then normalized to account for geometrical and illumination changes using information about the eye location. Specifically performance true positive by Ensambles RBF1 (ERBF1) increased on ± 13,86% measures up to RBF while ERBF2 by ± 15,93%. On the contrary the false negative rate decreased by amount of ±5,8% for ERBF1 and somewhat less to ±5,6% for ERBF2. When the connectionist ERBF model is coupled with an Inductive Decision Tree - C4.5 - the performance improves over the case while only the connectionist ERBF module is used

Automatic Raga Recognition in Hindustani Classical Music

Raga is the central melodic concept in Hindustani Classical Music. It has a complex structure, often characterized by pathos. In this paper, we describe a technique for Automatic Raga Recognition, based on pitch distributions. We are able to successfully classify ragas with a commendable accuracy on our test dataset.Comment: Seminar on Computer Music, RWTH Aachen, http://hpac.rwth-aachen.de/teaching/sem-mus-17/Reports/Alekh.pd

Scenario Approach for Image Processing in Smart City

Modern city is described by fast change of a situations and large volume of available data about it. One of principal data types are images (satellite pictures, video from surveillance cameras, etc.). Fast manual analysis of such data is often complicated or impossible. Widespread practice is development of analysis system for each separate problem (for example identification of car identification numbers or QR-codes) that leads to a number of difficulties; in particular, it is difficult to integrate and modify such systems. In article the structure of raster image analysis system (both single images and a video stream) is proposed. The system is developed taking into account peculiarities of input data and requirements imposed by the smart city. As a basis of system the set of algorithms, that implements all image analysis stages (preliminary processing, construction of feature space and classification) is proposed. That algorithms are elements of data processing scenarios. Usage of scenario approach, based on subject domain ontology, allows to significantly simplify adaptation of image processing system to the peculiarities of subject domain without limitation of allowed algorithms set. A example of application of the developed system for real-world problem is given