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Skin analysis is one of the most important procedures before medical cosmetology. Most conventional skin analysis systems are semi-automatic. They often require human intervention. In this study, an automatic facial skin defect detection approach is proposed. The system first detects human face in the facial image. Based on the detected face, facial features are extracted to locate regions of interest...
In this paper, we apply the principal component analysis (PCA) to extract significant image features and then incorporated them with the proposed two-phase fuzzy adaptive resonance theory neural network (Fuzzy-ART) for image content classification to overcome the gap between the low level features and high level semantic concepts. In general, Fuzzy-ART is an unsupervised clustering. Meanwhile, the...
In our daily life, it is much easier to distinguish which person is elder between two persons than how old a person is. When inferring a person's age, we may compare his or her face with many people whose ages are known, resulting in a series of comparative results, and then we conjecture the age based on the comparisons. This process involves numerous pairwise preferences information obtained by...
Analyzing the contents of an image and retrieving corresponding semantics are important in semantic-based image retrieval system. In this paper, we apply the principal component analysis (PCA) to extract significant image features and then incorporated them with the proposed Two-phase Fuzzy Adaptive Resonance Theory Neural Network (Fuzzy-ARTNN) for image content classification. In general, Fuzzy-ARTNN...
Abstract-Analyzing the contents of an image and retrieving corresponding semantics are important in semantic-based image retrieval system. In this paper, we apply the independent component analysis (ICA) to extract significant image features and then incorporated it with the proposed Two-phase Fuzzy Adaptive Resonance Theory Neural Network (Fuzzy-ARTNN) for image content classification. In general,...
With the purpose of designing a general learning framework for detecting human parts, we formulate this task as a classification problem over non-aligned training examples of multiple classes. We propose a new multi-class multi-instance boosting method, named MCMIBoost, for effective human parts detection in static images. MCMIBoost has two benefits. First, training examples are represented as a set...
Hyperthyroidism is a common thyroid disease. Graves' disease is the most common etiology with 70-80% of hyperthyroidism. Conventionally, a diagnosis requires weeks to confirm with blood tests. In this paper, we proposed a novel approach to diagnose Gravespsila disease in ultrasound images directly. We segment the thyroid regions, and utilize a high performance classifier to recognize the regions....
A lymph node (LN), which can resist virus and germs, is part of the lymphatic system that exists in the human body and every apparatus inside it. There are many kinds of pathological changes in LN. Metastatic is one of the important indexes to estimate the stage of malignant tumors. One convenient tool to observe LN is the use olf ultrasonic images. Clinical physicians judge a nosology by biopsy and...
The objective of this paper is to provide a complete solution to estimate the volume of the thyroid gland directly from US images. In this paper, the radial basis function (RBF) neural network is used to classify blocks of the thyroid gland; the integral region is further acquired by applying a specific region growing method to potential points. The parameters for evaluating the thyroid volume is...
Due to the vogue of digital cameras, it is easy to obtain digital images. And with the rapid development of digital image processing, database and internet technologies, how to efficiently manage a large amount of digital images become very important. Therefore, in this paper, we propose a novel method, which integrates the principal component analysis (PCA) and modular radial basis function (MRBF)...
The capability of robotic emotion recognition is an important factor for human-robot interaction. In order to facilitate a robot to function in daily live environments, a emotion recognition system needs to accommodate itself to various persons. In this paper, an emotion recognition system that can adapt to new facial data is proposed. The main idea of the proposed learning algorithm is to adjust...
Much research has shown that the definitions of within-class and between-class scatter matrices and regularization technique are the key components to design a feature extraction for small sample size problems. In this paper, we illustrate the importance of another key component, eigenvalue decomposition method, and a new regularization technique was proposed. In the hyperspectral image experiment,...
For a multiple classifiers system, a weighting policy is applied to fuse knowledge acquired by classifiers to arrive at an overall decision that is supposedly superior to that attainable by any one of them acting alone. The distance measured between the classifier output and its desired output can be used as a classifier performance indicator. By adopting this performance indicator, the rms and average...
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