The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Classification systems of retail products have recently been gaining more importance. There are many classes of retail products and the resemblance of these products makes the design of product recognition systems, which have many application areas, more challenging. In this paper, we present a comparison of different classification techniques that are widely used in computer vision for image classification...
A novel hyperspectral classification algorithm based on spectral-spatial feature extraction is proposed. First, spectral-spatial features are extracted by Gabor transform in PCA-projected space. Following that, Gabor-feature bands are partitioned into multiple subsets. Afterwards, the adjacent features in each subset are fused. Finally, the fused features are processed by recursive filtering before...
Augmentative and Alternative Communication (AAC) apps are apps that enable non-speech communicative forms. One class of AAC apps are speech-generating devices (SGDs), where icons/pictures are tapped to produce spoken words. These apps are widely used to support communication and language learning for individuals with disabilities such as autism spectrum disorder (ASD). Given that these apps are used...
The most common cause of blindness in the world by far is known to be the Glaucoma condition. The increase in the ratio of cup to the disc area and the thinning of retinal layers are the most common symptoms of Glaucoma. Functional and structural features of the eye should be examined in order to distinguish an eye with Glaucoma from a healthy eye. In this study, the texture information in Optical...
In this study, Sentinel-1A SAR imagery for land use/cover classification and its impacts on classification algorithms were addressed. Sentinel-1A imagery has dual polarization (VV and VH) and freely available from ESA. Istanbul was selected as the study region. After the pre-processing steps including the applying the precise orbit file, calibration, multilooking, speckle filtering and terrain correction,...
Fibromyalgia (FM) is a widespread painful disease that has a 2–8% prevalence. Its diagnosis is generally performed by American College of Rheumatology (ACR) criteria. However, these criteria are subjective and their reliability is controversial. In this study, painful stimulation and Transcutaneous Electrical Nerve Stimulation (TENS) were applied to both hands of healthy controls and FM patients and...
Classification is one of the most researched issues in Machine Learning. In this study, the Lorentzian Support Vector Machine (LSVM) method is proposed that performs classification in Lorentzian space. This proposed new classifier forms a hyperplane separating the classes based on the Lorentzian metric and maximize margins between nearest points to the hyperplane according to the Lorentzian distance...
Supervised classification methods have been widely used in the hyperspectral remote sensing image analysis. However, they require a large number of training samples to guarantee good performance, which costs a large amount of time and human labor, motivating researchers to reuse labeled samples from the mass of pre-existing related images. Transfer learning methods can adapt knowledge in the existing...
The biggest concern of Network is security. Intro find the tricks and tools of the Attackers. Data Mining techniques automatically learn the pattern of the tuples and Intelligent decision are made. Supervised learning methods finds the attack based on previous knowledge and unknown attacks are detected by using Unsupervised learning. Dos, Probe and Normal data are correctly detected by maximum Data...
Due to the variability of writing styles and to other problems related to the nature of Arabic scripts, the recognition of Arabic handwriting is still awaiting accurate results. Segmentation of Arabic handwritten words into graphemes poses a major challenge in Arabic handwriting recognition and is highly error prone. In this paper, we adopt the holistic approach which handles the whole word image...
Users of search engines interact with the system using different size and type of queries. Current search engines perform well with keyword queries but are not for verbose queries which are too long, detailed, or are expressed in more words than are needed. The detection of verbose queries may help search engines to get pertinent results. To accomplish this goal it is important to make some appropriate...
Classifying ancient Arabic manuscripts based on handwriting styles is one of the important roles in the field of paleography. Recognizing the style of handwriting in Arabic manuscripts helps in identifying the origin and date of ancient documents. In this paper we proposed using segmented letters from Arabic manuscripts to recognize handwriting style. Both Gabor Filters (GF) and Local Binary Pattern...
The “Nuclear Seed Recognition and Weed Segregation System (NSRWSS)” aims at simplifying the task of identification and classification of seed varieties using Image Processing techniques. Seed recognition and weed segregation consumes a lot of manual labor in seed production industries. NSRWSS can accomplish weed and damaged seed separation for various crops. Genetic purity, which is given top most...
Unknown awareness is very important for many applications such as face recognition. In a typical unknown aware classifier, an “unknown” label is assigned to strange test instances. This study proposes an unknown aware classifier known as UAkNN by extending the well-known kNN classifier. In UAkNN, unknown awareness is achieved by exploiting distances between instances of individual classes. These distances...
In this work, a new method for discrimination between normal and heart murmurs sound is presented. Statistical parameters, such as standard deviation (SD), are extracted from two datasets of heartbeats. Several classification technics, such as Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Naïve Bayes (NB), discriminative analysis, and classification tree, are used. Simulation results obtained...
Timely and accurate diagnosis of intraabdominal organ injuries due to trauma is critical. Computer Assisted Detection (CAD) systems are rapidly developing techniques to segment the organs or to detect the pathologies in medical applications; either automatically or semi-automatically. In this work, our aim is to propose and validate a CAD system which classifies injured kidney in Computed Tomography...
Task-based functional magnetic resonance imaging (tfMRI) is widely used to localize brain regions or networks in response to various cognitive tasks. However, given two groups of tfMRI data acquired under distinct task paradigms, it is not clear whether there exist intrinsic inter-group differences in signal composition patterns, and if so, whether these differences could be used for data discrimination...
Detection of brain metastases in patients with undiagnosed primary cancer is unusual but still an existing phenomenon. In these cases, identifying the cancer site of origin is non-feasible by visual examination of magnetic resonance (MR) images. Recently, radiomics has been proposed to analyze differences among classes of visually imperceptible imaging characteristics. In this study we analyzed 46...
In this study, a novel feature selection framework is proposed to simultaneously perform classification and clinical scores prediction of Parkinson's disease (PD) via multi-modal neuroimaging data. Specifically, a new feature selection model is devised to capture discriminative features to train support vector regression model for clinical scores (e.g., sleep scores and olfactory scores) prediction...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.