To improve speech recognition performance, acoustic feature transformation based on discriminant analysis has been widely used. For the same purpose, discriminative training of HMMs has also been used. In this letter we investigate the effectiveness of these two techniques and their combination. We also investigate the robustness of matched and mismatched noise conditions between training and e...

to prospect mineral deposits at regional scale, recognition and classification of hydrothermal alteration zones using remote sensing data is a popular strategy. due to the large number of spectral bands, classification of the hyperspectral data may be negatively affected by the hughes phenomenon. a practical way to handle the hughes problem is preparing a lot of training samples until the size ...

Neural Networks and SVM are recently being used in various kind of pattern recognition. As humans, it is easy to recognize numbers, letters, voices, and objects, to name a few. However, making a machine solve these types of problems is a very difficult task . Character Recognition has been an active area of research in the field of image processing and pattern recognition and due to its diverse...

In the talk I will presents an approach of visual shape recognition based onexemplars of attributed keypoints. The work may be seen as a refinementof a previous work [1]. The work is aimed at object shape categorizationby image semantic report. Training is performed by storing exemplarsof keypoints detected in labeled training images. Recognition is made bykeypoint matching ...

DiPietro et al (2002 Perception 31 1299-1312) reported a dramatic improvement in pigeons' recognition of partially occluded objects after the birds had been trained to recognize objects that were placed on top of another surface. Here, we investigated whether training with partially erased stimuli or with notched stimuli that had a thin gap between the object and another surface would similarly...

Handwritten digit recognition can be categorized as a classification problem. Probabilistic Neural Network (PNN) is one of the most effective and useful classifiers, which works based on Bayesian rule. In this paper, in order to recognize Persian (Farsi) handwritten digit recognition, a combination of intelligent clustering method and PNN has been utilized. Hoda database, which includes 80000 P...

Many classic and contemporary face recognition algorithms work well on public data sets, but degrade sharply when they are used in a real recognition system. This is mostly due to the difficulty of simultaneously handling variations in illumination, image misalignment, and occlusion in the test image. We consider a scenario where the training images are well controlled and test images are only ...

This paper focuses on discriminative trainings (DT) applied to ivectors after Gaussian probabilistic linear discriminant analysis (PLDA). If DT has been successfully used with non-normalized vectors, this technique struggles to improve speaker detection when i-vectors have been first normalized, whereas the latter option has proven to achieve best performance in speaker verification. We propose...