1,720,991 research outputs found
Faculty of Electronics, Telecommunications and Information Technology,
No full textAbstract- This paper presents an optimum color conversion from the 3D RGB space into a 2D selected space to the purpose of pattern recognition. The method is based on the Karhunen-Loève transform (KLT), also known as Principal Component Analysis (PCA). The resulted 2D space is defined by the two color components (called C1 and C2), corresponding to the two largest eigenvalues of the RGB pixel covariance matrix. Using the above color projection technique, we propose a color face recognition system based on feature fusion of the C1 and C2 components and a concurrent neural network classifier. The proposed system is experimented for a color face database containing 3520 color images of 151 subjects. We also present a color image segmentation using pixel clustering in the 2D color space by means of a self-organizing neural network. The new 2D color projection model may have wide applications in the areas of color-based pattern recognition
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Face detection in color images using fusion of the chrominance and luminance channel decisions
No full text
An Ensemble of Deep Convolutional Neural Networks for Drunkenness Detection Using Thermal Infrared Facial Imagery
No full textA Deep Learning Model with Long Short-Term Memory (DLSTM) for Prediction of Currency Exchange Rates
No full text
- …
