as the information carried in a high spatial resolution image is not represented by single pixels but by meaningful image objects, which include the association of multiple pixels and their mutual relations, the object based method has become one of the most commonly used strategies for the processing of high resolution imagery. this processing comprises two fundamental and critical steps towar...

According to the fundamental goal of remote sensing technology, the image classification of desired sensors can be introduced as the most important part of satellite image interpretation. There exist various algorithms in relation to the supervised land use classification that the most pertinent one should be determined. Therefore, this study has been conducted to determine the best and most su...

background one of the main objects in medical science is diagnosis the diseases and classification the patients to different classes. consequently according to the above the patients that set in one classes should have maximum similarity with each other. discrimination and classification analysis have been frequently used in medical data for diagnosis and prognostic of the disease. the wrong in...

In the last decade, high profile financial frauds committed by large companies in both developed and developing countries were discovered and reported. This study compares the performance of five popular statistical and machine learning models in detecting financial statement fraud. The research objects are companies which experienced both fraudulent and non-fraudulent financial statements betw...

Graph neural networks have a wide range of applications, such as citation networks, social and knowledge graphs. Among various graph analyses, node classification has garnered much attention. While many the recent network embedding models achieve promising performance, they usually require sufficient labeled nodes for training, which does not meet reality that only few are available in novel cl...

Introduction: This research was meant to provide a model for COPD diagnosis and to classify the cases into phenotypes; General COPD, Chronic bronchitis, Emphysema, and the Asthmatic COPD using a Bayesian Network (BN). Methods: The model was constructed through developing the Bayesian Network structure and instantiating the parameters for each of the variables. In order to validate the achiev...

urban expansion model (uem) was adapted to simulate urbanization which implements geospatial information systems (gis), artificial neural networks (anns) and remote sensing (rs). two satellite imageries with specific time interval, socio-economic and environmental variables have been employed in order to simulate urban expansion. socio-economic and environmental variables were used as inputs wh...

handwritten digit recognition can be categorized as a classification problem. probabilistic neural network (pnn) is one of the most effective and useful classifiers, which works based on bayesian rule. in this paper, in order to recognize persian (farsi) handwritten digit recognition, a combination of intelligent clustering method and pnn has been utilized. hoda database, which includes 80000 p...