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检索条件"任意字段=1st International Conference on Computational Intelligence in Pattern Recognition, CIPR 2019"

共 103 条记录，以下是11-20 订阅

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Fast Adaptive Decision-Based Mean Filter for Removing Salt-and-Pepper Noise in Images 1st

Fast Adaptive Decision-Based Mean Filter for Removing Salt-a...

引用

1st international conference on computational intelligence in pattern recognition, cipr 2019

作者： Halder, Amiya Sengupta, Supravo Bhattacharya, Pritam Sarkar, Apurba St. Thomas College of Engineering and Technology Kolkata700023 India IIEST Shibpur Howrah711103 India

ISBN: (纸本)9789811390418

This paper presents a very simple and extremely fast approach to remove salt-and-pepper noise from digital images. Initially, the pixels are roughly divided into two classes, noisy pixels and non-noisy pixels based on the intensity values. Then, the second stage is to eliminate the noise from the images. In this stage, only the noise pixels are processed and the noise-free pixels remain unchanged. This method takes four non-noisy pixels in four directions around noisy pixel and predicts the intensity value of the noisy candidate. This proposed method is suitable to be implemented in consumer electronics products such as digital televisions or digital cameras. Experiments and comparisons demonstrate that our proposed filter has very low detection error rate and high restoration quality. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Median filters

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Numerical Integration Based Contrast Enhancement Using Simpson’s Method 1st

Numerical Integration Based Contrast Enhancement Using Simps...

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1st international conference on computational intelligence in pattern recognition, cipr 2019

作者： Halder, Amiya Bhattacharya, Pritam Shah, Nikita Department of CSE St. Thomas’ College of Engineering and Technology 4 D. H. Road Kidderpore Kolkata700023 India

ISBN: (纸本)9789811390418

This paper is based on mathematical numerical integration method and provides an efficient algorithm for improving the contrast of an image. The aim of this unique method is to use neighboring pixel information and process them in accordance with mathematics (Simpson’s 13 rd rule) to improve contrast of images. Simpson’s rule is a numerical integration method for the accurate approximation of definite integrals. It gives the exact results for polynomials of degree three or less. We use the neighboring pixel information, interpolate among them, and produce the enhanced pixel information. Various parameters like Root Mean Square Error (RMSE), Peak-Signal-to-Noise-Ratio (PSNR) and structural Similarity Index (SSIM) are used to measure the quality of the images. The experimental results of the proposed method are compared with some existing methods for further validation. Also, the computational time of the proposed method is much less as compared to the different existing methods. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Image enhancement

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Support vector machine classifier for pattern recognition

Support vector machine classifier for pattern recognition

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1st international conference on Informatics and computational intelligence, ICI 2011

作者： Farhan, Mohammad Abdullah, Mujeeb Kassem, Ghulam Akbar, Siddique Institute of Engineering and Computing Sciennces University of Science Ant Technology Bannu Pakistan University of Science and Technology Bannu Pakistan Shanghai China Gomal University Pakistan

ISBN: (纸本)9780769546186

Automatiuc speech recognition is carried out by Mel-frequency cepstral coefficient (MFCC). Linearly-spaced at low and logarithmic-spaced filters at higher frequencies are used to capture the characteristics of speech. Multi-layer perceptrons (MLP) approximate continuous and non-linear functions. High dimensional patterns are not permitted due to eigen-decomposition in high dimensional image space and degeneration of scattering matrices in small size sample. Generalization, dimensionality reduction and maximizing the margins are controlled by minimizing weight vectors. Results show good pattern by SVM algorithm with Mercer kernel. © 2011 IEEE.

关键词： Support vector machines

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A Cascaded Method to Reduce the computational Burden of Nearest Neighbor Classifier 1st

A Cascaded Method to Reduce the Computational Burden of Near...

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1st international conference on computational intelligence and Informatics (ICCII)

作者： Kumar, R. Raja Viswanath, P. Bindu, C. Shobha Rajeev Gandhi Coll Engn & Technol Nandyal India IIIT Chittoor Chittoor India JNTUA Coll Engn Anantapur Andhra Pradesh India

ISBN: (纸本)9789811024719;9789811024702

Nearest neighbor classifiers demand high computational resources, i.e., time and memory. Two distinct approaches are followed by researchers in pattern recognition to reduce this computational burden. The first approach is reducing the reference set (training set) and the second approach is dimensionality reduction which is referred to as prototype selection and feature reduction (a.k.a feature extraction or feature selection), respectively. In this paper, we cascaded the two methods to achieve the reduction in both directions. The experiments are done on the bench mark datasets, and the results obtained are satisfactory.

关键词： Nearest neighbor classifiers Prototype selection pattern recognition Feature selection

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Voice-Based Gender Identification Using Co-occurrence-Based Features 1st

Voice-Based Gender Identification Using Co-occurrence-Based ...

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1st international conference on computational intelligence in pattern recognition, cipr 2019

作者： Ghosal, Arijit Pathak, Chanda Singh, Pinki Dutta, Suchibrota Department of Information Technology St. Thomas’ College of Engineering and Technology KolkataWest Bengal700 023 India Department of Information Technology and Mathematics Royal Thimphu College Thimphu11001 Bhutan

ISBN: (纸本)9789811390418

Automatic detection of gender based on audio is gaining its popularity day-by-day because of its several applications in several domains. But most of the past research works are limited to differentiate male and female voice toward gender detection from audio signal. Very less work has been performed for gender identification considering trans-gender also. As trans-gender has received legal recognition, it is expected that a good gender detection system should be able to identify all the three genders. In this work some judiciously chosen acoustic features have been employed to identify all the three genders. This proposed feature set is of small dimensional to keep computational complexity low. Low-level time-domain acoustic features like short time energy, spectral flux and audio features belonging to frequency domain as well as skewness have been used here. Co-occurrence-based approach has been applied further for precise observation of these features. Neural network, Naïve Bayes and k-nearest neighbor have been used for classification purpose. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Frequency domain analysis

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Classification of Ball Mill Acoustic for Predictive Grinding Using PCA 1st

Classification of Ball Mill Acoustic for Predictive Grinding...

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1st international conference on computational intelligence in pattern recognition, cipr 2019

作者： Sen, Sonali Bhaumik, Arup Kumar Sil, Jaya Department of Computer Science St. Xavier’s College Kolkata India Department of Computer Science RCCIIT Kolkata India Department of Computer Science IIEST Kolkata India

ISBN: (纸本)9789811390418

The aim of this paper is to design a classification model to predict the terminating condition of a ball mill in raw material specific application. The acoustics of a running ball mill in different phases of grinding is analyzed to derive the signatures of the signal with different raw materials. Here we classify the sound signatures of the mill, which helps us to predict the characteristics of different running conditions with different size distribution of the materials. Using stereophonic microphones acoustic of a running ball mill is captured. The acoustic signal is then fragmented based on one rotation of the mill and saved in an appropriate format for further analysis. The statistical moments of each fragment are taken as the parameters and applied Principal Component Analysis to select the important features. Finally, we classify the analyzed data to find the running state of the mill. The classification model is tuned in order to achieve an experimental result from the simulated result. Also in real time the model has been tested. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Principal component analysis

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Unidentified Input Observer: Comparative study Through Block Pulse Function and Hybrid Function 1st

Unidentified Input Observer: Comparative Study Through Block...

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1st international conference on computational intelligence in pattern recognition, cipr 2019

作者： Ganguly, Anindita Chowdhury, Tathagata Roy Ghosh, Suman Kumar Panigrahi, Aishik Chakraborty, Nilotpal Ghosh, Anirudhha Ganguly, Neelakshi Department of Electrical Engineering Guru Nanak Institute of Technology KolkataWest Bengal700114 India Department of Electrical Engineering St. Thomas College of Engineering and Technology KolkataWest Bengal700023 India Department of Electrical Engineering Indian Institute of Technology DhanbadJharkhand826004 India

ISBN: (纸本)9789811390418

In many systems, the inputs cannot be exactly identified. For the implementation of certain desirable control objectives, the inputs and the states of such systems are estimated. In this paper to estimate the desired quantities, observers are designed and linear systems are studied with unidentified inputs. To make the state and input estimation possible, the use of delayed observers is considered here to enlarge the class of systems. The design procedure involves the design of unidentified input observer with appropriate choice of design matrices. The necessary and sufficient conditions proving the existence of such observers are also described in this paper. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Linear systems

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Face Identification via strategic Combination of Local Features 1st

Face Identification via Strategic Combination of Local Featu...

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1st international conference on computational intelligence in pattern recognition, cipr 2019

作者： Rakshit, Rinku Datta Kisku, Dakshina Ranjan Asansol Engineering College Vivekananda Sarani Kanyapur AsansolWest Bengal713305 India National Institute of Technology Mahatma Gandhi Road A-Zone DurgapurWest Bengal713209 India

ISBN: (纸本)9789811390418

Face identification systems that use a single local descriptor often suffer from lack of well-structured, complementary and relevant facial descriptors. To achieve notable performance, a face identification system is presented, which makes use of multiple representations of a face by means of different local descriptors derived from Local Binary pattern (LBP) and Local Graph structure (LGS). Then, max, average and L2 pooling operations are applied on each representation of face image to scale down the features. Further, different representations are combined together and formed a strategically concatenated feature vector. Three classifiers including two correlation based and k-nearest neighbor (kNN) are used to produce matching proximities which are used to characterize a probe user with rank identity. The produced ranks are then fused together using rank level fusion techniques. The experimental results determined on the Extended Yale face B database and the Plastic Surgery database are encouraging and convincing. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Local binary pattern

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About gradient operators on hyperspectral images

About gradient operators on hyperspectral images

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1st international conference on pattern recognition Applications and Methods, ICPRAM 2012

作者： Moreno, Ramón Graña, Manuel Computational Intelligence Group University of the Basque Country San Sebastián Spain

ISBN: (纸本)9789898425980

Gradient operators allow image segmentation based on edge information. Gradient operators based on chromatic information may avoid apparent edges detection due to illumination effects. This paper proposes the extension of chromatic gradients defined for RGB color images to images with n-dimensional pixels. A spherical coordinate representation of the pixel's content provides the required chromatic information. The paper provides results showing that gradient operators defined on the spherical coordinate representation effectively avoid illumination induced false edge detection.

关键词： Edge detection

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Automatic Indonesian's Batik pattern recognition Using SIFT Approach 1st

Automatic Indonesian's Batik Pattern Recognition Using SIFT ...

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1st international conference on Computer Science and computational intelligence (ICCSCI)

作者： Nurhaida, Ida Noviyanto, Ary Manurung, Ruli Arymurthy, Aniati M. Mercu Buana Univ West Jakarta 16550 Indonesia Univ Indonesia Depok 16424 Indonesia

Batik is a traditional clothwith unique patterns applied to fabric using a wax-resist dyeing technique. Aside from preserving this rich cultural heritage, the automated recognition of Batik patterns would enable many interesting applications. This paper introduces an approach to batik pattern recognition using the Scale Invariant Feature Transform (SIFT) as a feature extraction method. The challenging issues that arise are due to the highly symmetrical and repetitive properties of batik patterns. The Hough transform, as an evidence-based method of object detection, is applied to handle mismatched keypoints resulting from symmetrical and repetitive patterns of batik. On a collection of 120 batik images generated from 20 basic batik patterns, the proposed method showsan improvement over the original SIFT matching method with an equal error rate of 8.47%. (C) 2015 Published by Elsevier B.V.

关键词： Batik motif SIFT voting Hough transform

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