there are many difficulties facing a handwritten Arabic recognition system such as unlimited variation in character shapes. this paper describes a new method for handwritten Arabic character recognition. We propose a ...
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In this paper, an advanced hierarchical model has been proposed to produce a more effective character recognizer based on the probability of occurrence of the patterns. New definitions such as crucial parts, efficienc...
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Cuneiform symbols represent a complex problem in patternrecognition, in particular for OCR (optical character recognition) due to challenges related to cuneiform-like character distortion and font heterogeneity. this...
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ISBN:
(纸本)9781538613528;9781538644607
Cuneiform symbols represent a complex problem in patternrecognition, in particular for OCR (optical character recognition) due to challenges related to cuneiform-like character distortion and font heterogeneity. this paper proposes new approaches to recognise Assyrian cuneiform characters using OCR to classify the symbols. as a new way to recognize the Assyrian letters by dealing with symbols of complex character. the dataset utilised consists of 16patterns to reflect all probabilities associated with each cuneiform symbol related to their shape and directions, assuming each character consists of a set of symbols. Polygon approximation techniques are used to generate feature vectors for the classification tasks. the proposed method obtains classification ratios up to 91% depending on the algorithm used for the feature vector.
Protein fold recognition has been the focus of computational biologists for many years. In order to map a protein primary structure to its correct 3D fold, we introduce in this paper a machine learning paradigm that w...
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ISBN:
(纸本)0769525210
Protein fold recognition has been the focus of computational biologists for many years. In order to map a protein primary structure to its correct 3D fold, we introduce in this paper a machine learning paradigm that we entitled 11 structural hidden Markov model" (SHMM). We show how the concept of SHMM can efficiently use the protein secondary structure during the fold recognition task. Experimental results showed that the SHMM outperforms the SVM with a 6% improvement in the average accuracy. However, because in this application the two classifiers are not correlated, therefore their combination based on the highest rank criterion boosted the SHMM average accuracy with 10%.
Pixel force field (PFF) is a novel image representation where at each pixel a two-dimensional vector is defined for representing interaction of pixels. the vector is oriented to the center of the region composed of pi...
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ISBN:
(纸本)0769525210
Pixel force field (PFF) is a novel image representation where at each pixel a two-dimensional vector is defined for representing interaction of pixels. the vector is oriented to the center of the region composed of pixels having the same qualitative property, such as color and gray-scale level. Using the pixel force field and improved live-wire segmentation technique the task of interactive road extraction from remote sensing images is solved.
In this paper we propose a new probabilistic approach to red eye detection and correction. It is based on stepwise refinement of a pixel-wise red eye probability map. Red eye detection starts with a fast non red eye r...
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ISBN:
(纸本)0769525210
In this paper we propose a new probabilistic approach to red eye detection and correction. It is based on stepwise refinement of a pixel-wise red eye probability map. Red eye detection starts with a fast non red eye region rejection step. A classification step then adjusts the probabilities attributed to the detected red eye candidates. the correction step finally applies a soft red eye correction based on the resulting probability map. the proposed approach is fast and allows achieving an excellent correction of strong red eyes while producing a still significant correction of weaker red eyes.
this paper proposes a novel part-based character recognition method for a new topic of RMB (renminbi bank note, the paper currency used in China) serial number recognition, which is important for reducing financial cr...
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Machine learning methods are used today mostly for recognition problems. Convolutional Neural Networks (CNN) have time and again proved successful for many image processing tasks primarily for their architecture. In t...
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Accurately predicting the binding affinities of large sets of diverse molecules against a range of macromolecular targets is an extremely challenging task. the scoring functions that attempt such computational predict...
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ISBN:
(纸本)9783642341236
Accurately predicting the binding affinities of large sets of diverse molecules against a range of macromolecular targets is an extremely challenging task. the scoring functions that attempt such computational prediction exploiting structural data are essential for analysing the outputs of Molecular Docking, which is in turn an important technique for drug discovery, chemical biology and structural biology. Conventional scoring functions assume a predetermined theory-inspired functional form for the relationship between the variables that characterise the complex and its predicted binding affinity. the inherent problem of this approach is in the difficulty of explicitly modelling the various contributions of intermolecular interactions to binding affinity. Recently, a new family of 3D structure-based regression models for binding affinity prediction has been introduced which circumvent the need for modelling assumptions. these machine learning scoring functions have been shown to widely outperform conventional scoring functions. However, to date no direct comparison among machine learning scoring functions has been made. Here the performance of the two most popular machine learning scoring functions for this task is analysed under exactly the same experimental conditions.
In this paper, the algorithm for thinning of grey-scale images is proposed that is based on a pseudo-distance map (PDM). the PDM is a simplified distance map of gray-scale image and uses only that features of image an...
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ISBN:
(纸本)0769525210
In this paper, the algorithm for thinning of grey-scale images is proposed that is based on a pseudo-distance map (PDM). the PDM is a simplified distance map of gray-scale image and uses only that features of image and objects that are necessary to build a skeleton. the algorithm works fast for large gray-scale images and allows constructing a high quality skeleton.
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