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Biomedical research in last decade or so has seen the development of highly accurate algorithms focused on the detection and classification of the brain tumor into malignant or benign. As a result of these advancements a new research direction has emerged which focuses on categorizing the brain tumors based on their types, such as Glioma, Metastases, and Meningioma etc. In this paper, we present a...
In this paper we present an automatic method for ultrasound-based early detection of pregnancy in pigs, which is a crucial information for commercial pig farming. We employ a strategy of region-based classification within multiple segmentation hierarchies which is able to efficiently find target structures in a large set of possible segmentations. Furthermore, we present a novel set of border features,...
For personal identification, the biometric systems based on finger-vein pattern have been successfully used in many applications. The concern for the system efficiency over a large database should not be negligible in the real situation. So, categorizing the finger-vein images to different classes is helpful for reducing pattern matching cost. In this paper, we propose a level-based framework for...
Many real world applications contain a decision making process which can be regarded as a pattern classification stage. Various pattern classification techniques have been introduced in the literature ranging from heuristic methods to intelligent soft computing techniques. In this paper, we focus on the latter and in particular on fuzzy rule-based classification algorithms.We show how an effective...
This paper, presents a new cephalometric landmark localization method based on combining two classifier results. Initially, a classifier based on histograms of oriented gradients makes a first estimation of the potential windows, and then a second classifier, based on histograms of gray profile, classifies the detected windows. By combining the results of these two classifiers, final decision is made...
High quality of compressed image is required in many fields such as remote sensing and medicine. A near-lossless image compression algorithm is proposed in this paper. The algorithm takes advantage of the effects of the distribution of pixels on compression ratio. The pixels are classified row by row firstly, and the classification result is recorded in a mask image. After that the image data is decomposed...
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