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To improve the accuracy of surface defect detection, an approach of defect inspection based on visual saliency map and Support Vector Machine(SVM) is proposed. Monochrome fabric defect images are taken as examples in this paper. By analyzing the visual saliency maps of these images, the global associated value and the background associated value are extracted as the two features. After being normalized,...
With the rapid development of MOOC platform, MOOC resource recommendation technology is emerging to improve the learner's learning efficiency. The traditional collaborative filtering resource recommendation technique is ineffective when dealing with sparse data and cannot accurately handle the high dimension attributes of online learning users, which result in low efficiency of resource recommendation...
This paper proposes a speech/music classification system based on i-vector. An analysis of two classification methods, namely cosine distance score (CDS) and support vector machine (SVM) is performed. Two session compensation methods, within-class covariance normalization (WCCN) and linear discriminant analysis (LDA) are also discussed. The performance of proposed systems yields better results compared...
We present a method for automatically learning object and state models, which can be used for recognition in an augmented reality task guidance system. We assume that the task involves objects whose appearance is fairly consistent, but the background may vary. The novelty of our approach is that the system can be automatically constructed from examples of experts performing the task. As a result,...
Studies have shown that a motor imagery electro encephalogram (EEG)-based brain-computer interface (BCI) system can be used as a rehabilitation tool for stroke patients. Efficient classification of EEG from stroke patients is fundamental in the BCI-based stroke rehabilitation systems. One of the most successful algorithms for EEG classification is the common spatial patterns (CSP). However, studies...
Adaptation is an essential capability for intelligent robots to work in new environments. In the learning framework of Programming by Demonstration (PbD) and Reinforcement Learning (RL), a robot usually learns skills from a latent feature space obtained by dimension reduction techniques. Because the latent space is optimized for a specific environment during the training phase, it typically contains...
This report presents results from the Video Person Recognition Evaluation held in conjunction with the 11th IEEE International Conference on Automatic Face and Gesture Recognition. Two experiments required algorithms to recognize people in videos from the Point-and-Shoot Face Recognition Challenge Problem (PaSC). The first consisted of videos from a tripod mounted high quality video camera. The second...
In particular for “low resource” Keyword Search (KWS) and Speech-to-Text (STT) tasks, more untranscribed test data may be available than training data. Several approaches have been proposed to make this data useful during system development, even when initial systems have Word Error Rates (WER) above 70%. In this paper, we present a set of experiments on low-resource languages in telephony speech...
In order to solve the small sample problems and the linear inseparable problems caused by some nonlinear factors, this paper proposed a method to generate multiple virtual samples similar to the original images by its class, then all virtual samples were combined as a new database for training. The method not only helps to increase more samples, but strengthens the reliance of virtual samples on the...
A gender classification system uses human face from a given image to tell the gender of the given person. An effective gender classification approach is able to promote the improvement of many other applications, including image/video retrieval, security monitor, human-computer interaction, etc. In this paper, a method for gender classification task in frontal face images based on stacked-autoencoders...
We present a face recognition method based on sparse representation for recognizing 3D face meshes under expressions using low-level geometric features. First, to enable the application of the sparse representation framework, we develop a uniform remeshing scheme to establish a consistent sampling pattern across 3D faces. To handle facial expressions, we design a feature pooling and ranking scheme...
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