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Luis A. Alexandre
RGB-D data is getting ever more interest from the research community as both cheap cameras appear in the market and the applications of this type of data become more common. A current trend in processing image data is the use of convolutional neural networks (CNNs) that have consistently beat competition in most benchmark data sets. […]
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Syed Amer Zawad
This paper was conducted to analyze the performance benefits of parallelizing the Adaptive Weighted Sub-patterned Principle Component Analysis (Aw SP PCA) algorithm, given that the algorithm is implemented so as to retain the accuracy from its serialized version. The serialized execution of this algorithm is analyzed first and then compared against its parallel implementation, both […]
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Donald Lloyd van Blommestein
This thesis brings together productivity and risk assessments through innovative design, development and evaluation of a unique system for retrieving and analysing data. In the past, although the link between them is well-documented, these assessments have largely been dealt with as separate antagonist entities. A broad evaluation of the existing traditional and technological support systems […]
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Viragkumar N. Jagtap, Shailendra K. Mishra
Handwriting recognition is having high demand in commercial & academics. In recent years lots of good work has been done on hand written digit recognition to improve accuracy. Handwritten digit recognition system needs larger dataset and long training time to improve accuracy & reduce error rate. Training of Neural Networks for large data sets is […]
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Neelima Gogineni, C Ganga Bhavani, V S Giridhar Akula
Image recognition and segmentation techniques are playing key role in the field of image processing. Present researchers are working on the design concepts of accurate image processing. This paper explains the method for designing of accurate image processing with the help of the principle called automatic construction of tree structural image transformation and graphics processing […]
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Fu Jie Huang
In this work, we describe an application of convolutional networks to object classification and detection in images. The task of image based object recognition is surveyed in the first chapter. Its application in internet advertisement is one of the main motivations of this work. The architecture of the convolutional networks is described in details in […]
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Greg Durrett, Taylor Berg-Kirkpatrick
Hidden Semi-Markov Models (HSMMs) are powerful generalizations of Hidden Markov Models that have been effectively employed in tasks such as machine translation and optical character recognition. A principal computational bottleneck on these systems as applied to optical character recognition [5] is the need to compute emission probabilities for a large number of possible model states. […]
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Abhishek Sinha
Iris recognition is quite a computation intensive task with huge amounts of pixel processing. After the image acquisition of the eye, Iris recognition is basically divided into Iris localization, Feature Extraction and Matching steps. Each of these tasks involves a lot of processing. It thus becomes essential to improve the performance of each step to […]
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Ricardo J. Barrientos
Nowadays, similarity search is becoming a field of increasing interest because these kinds of methods can be applied to different areas in computer science and engineering, such as voice and image recognition, text retrieval, and many others. However, when processing large volumes of data, query response time can be quite high. In this case, it […]
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Sean Patrick Parker
Image recognition and classification is one of the primary challenges of the machine learning community. Recent advances in learning systems, coupled with hardware developments have enabled general object recognition systems to be learned on home computers with graphics processing units. Presented is a Deep Belief Network engineered using NVIDIA’s CUDA programming language for general object […]
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Salih Cihan Tek, Muhittin Gokmen
In this paper, we present a GPU accelerated face recognition framework using CUDA. We use weighted regional LBP histograms as features and k-nearest neighbour (k-NN) algorithm for classification. Our first contribution is to present an efficient way to compute LBP values from an input image and construct weighted regional LBP histograms in GPU using a […]
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Panagiotis Afxentis, Alicia Sanchez Crespo, Ying Zhang
This paper presents the GPU mapping of the recognition algorithm of a Convolution Neural Network (CNN). This work is based on a C-implementation of the application. The mapping to GPU was performed through different approaches which are explained in detail. The improvements achieved by each approach are presented as well as the overall speed up […]
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