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Recently the development of brain-computer interface applications has drawn the attention of research community as it can assist physically challenged people to communicate with their brain electroencephalogram (EEG) signal. In this paper, a Brain-Computer Interface (BCI) is designed using electroencephalogram (EEG) signals where the subjects have to think of only a single mental task. The presented...
Exploiting resource reusability and low precision in neural networks is a promising approach to achieve energy efficient computational platforms. This research presents two generalizable approaches to reuse resources in feed-forward neural networks and demonstrated on extreme learning machines. In the first approach, coalescing, a single stack of neuronal units perform both feature extraction and...
In this paper, we propose a palmprint recognition scheme using histograms of sparse codes (HSC) as a new feature for palmprint image. In the feature extraction stage, the HSC feature is obtained by computing sparse codes for a given dictionary from a palmprint image, which results in a feature image. In the feature encoding stage, a hash table is designed from the feature image using the binary hashing...
A novel approach of an embedded FPGA-based design for feature extraction using reconfigurable rotated wavelet transform (RWT) for various classification schemes is proposed. A new set of filter bank coefficients is generated by rotating a standard 1D discrete wavelet filter (DWF) in order to overcome shortcomings inherent in conventional ways of feature extraction such as discrete wavelet transform...
A face recognition system which represents each image as a superposition of the dominant components in two transform domains is proposed. The Discrete Wavelet Transform (DWT) and the Discrete Cosine Transform (DCT) are the two domains. By the end of the Training mode, each pose in the gallery will have two final matrices. Feature Extraction step in the Training includes transforming the preprocessed...
Command extraction from human beings becomes easier for a machine if it can analyze the non verbal ways of communication such as emotions. This paper focuses on improving the efficiency of extracting emotion from human facial expression images. The features that were extracted in this experiment were obtained from JAFFE (Japanese Female Facial Expression) database which includes 213 images of different...
A new approach based on applying the Two Dimensional Discrete Multiwavelet Transform (2D DMWT) to the partitioned faces is proposed in this paper for face recognition. First, the input facial image is divided into six parts in the preprocessing step to reduce the effect of the unnecessary information (background) on the system performance. Then, the 2D DMWT is applied to each part for feature extraction...
The overall aim of the proposed skin lesions classification method is to improve the quality and accuracy of existing skin diagnostic system by establishing superior feature extraction and classification of skin lesions from standard digital images. At first, images of skin lesions are pre-processed by resizing, removing hair, removing noise by filtering and enhancing contrast. Rather than using RGB/HSV/YCbCr...
This paper presents the current state of a novel event-based surveillance framework for real-time detection and tracking of the person-of-interest with IP PTZ network camera. Formulating the problem in a (non-linear) Bayesian filtering framework in combination with Convolutional Neural Networks (CNN), we develop dynamical and adaptive approaches for identifying the Person-of-Interest(PoI) from its...
Motivated by limited availability of training data for practical implementation of a synchronous Brain computer interface (BCI), the paper proposes a novel EEG-based framework consisting of two separate (partially coupled) filters running in parallel: (i) The Progressive Filter: An efficient but computationally extensive combination of feature extraction and classification that uses new arriving epochs...
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