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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Julia Moehrmann, Stefan Bernstein, Thomas Schlegel, Gunter Werner, Gunther Heidemann
Image recognition systems require large image data sets for the training process. The annotation of such data sets through users requires a lot of time and effort, and thereby presents the bottleneck in the development of recognition systems. In order to simplify the creation of image recognition systems it is necessary to develop interaction concepts […]
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Maurice Peemen, Bart Mesman, Henk Corporaal
From the desire to update the maximum road speed data for navigation devices, a speed sign recognition and detection system is proposed. This system should prevent accidental speeding at roads where the map data is incorrect for example due to construction work. Multiple examples of road sign classification systems already exist but none uses a […]
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Kailash Devrari, K.Vinay Kumar
Fast face detection is one of the key components of various computer vision applications. Viola-Jones algorithm provides a good and fast detection for low and medium resolution images. This paper proposes a new and fast approach to perform real time face detection. The proposed method includes the enhanced Haar-like features and uses SVM for training […]
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Kwang-Ting (Tim) Cheng, Yi-Chu Wang
As GPU becomes an integrated component in handheld devices like smartphones, we have been investigating the opportunities and limitations of utilizing the ultra-low-power GPU in a mobile platform as a general-purpose accelerator, similar to its role in desktop and server platforms. The special focus of our investigation has been on mobile GPU’s role for energy-optimized […]
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