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In this work, we primarily aim at estimating the performance of SVM-based gender recognition using widely used DCT and LBP facial features, as faithful as possible. The SVM classifier has been trained and cross-validated on the FERET database containing 2720 instances, while for testing, the LFW database containing over 13000 instances has been used. We have observed that the over 95% cross-validation...
Humans carry out object recognition as a very primitive task. However, knowing all the detailed information regarding an object is mostly not possible. Therefore, object recognition and linking the object to associated data is a popular research area. In this study, we have measured leaf recognition performances of different feature and data sets using image processing techniques. We have studied...
In this study, we have experimented with different image and shape descriptors on the automatic leaf recognition problem. We have studied the effects of gross shape descriptors, Fourier descriptors, multiscale distance descriptors, and the combination of these on the leaf recognition performance using two different datasets. We have achieved 94.62% recognition performance on Flavia, comparable to...
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