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Sparse Representation-based Classifier (SRC) is less sensitive to the shortage of data and the selection of feature space. In this paper, SRC is adopted to perform automatic analysis of tongue substance color and coating color which is considered as small dataset classification task. Firstly, for both training samples and testing samples, the tongue body regions are segmented, the regions of tongue...
While e-commerce has grown substantially over last several years, more and more people are utilizing this popular channel to purchase products and services. Thus the ability to predict user demographics, including gender, age and location has important applications in advertising, personalization, and recommendation. In this paper, we aim to automatically predict the users' genders based on their...
Effective far-range traversable region detection is a fundamental issue for mobile robots. However, the performance of traditional methods is limited as distance estimation of stereovision system is unreliable beyond 10–15m. In this paper, we proposed a far-range traversable region detection algorithm based on near-to-far self-supervised learning. In the algorithm, superpixel segmentation is employed...
Eye detection is a hot research topic in computer vision for its wide applications in human-computer interaction, face and iris recognition, etc. However, robust eye detection is still a grand challenge due to the numerous appearance variations of eye images in real-world applications. In this paper, we present a novel local surface curvature analysis method to deal with this problem. Firstly, by...
Spoof detection is a critical function for iris recognition because it reduces the risk of iris recognition systems being forged. Despite various counterfeit artifacts, cosmetic contact lens is one of the most common and difficult to detect. In this paper, we proposed a novel fake iris detection algorithm based on improved LBP and statistical features. Firstly, a simplified SIFT descriptor is extracted...
Feature representation and classification are two key steps for face recognition. A novel method for face recognition was presented based on combination of PCA (principal component analysis), LDA (linear discriminate analysis) and SVM (support vector machine). PCA and LDA combination was used for feature extraction and SVM were used for classification. The normalization had been done to eliminate...
Question classification plays a crucial important role in the question answering system. Recent research on question classification for open-domain mostly concentrates on using machine learning methods to resolve the special kind of text classification. This paper presents our research about Chinese question classification using machine learning method and gives our approach based on SVM and semantic...
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