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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1-10 订阅

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

1st International Conference on Computational Intelligence i...

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

ISBN: (纸本)9789811390418

The proceedings contain 88 papers. The special focus in this conference is on computational intelligence in pattern recognition. The topics include: Classification of Speech and Song Using Co-occurrence-Based Approach;Intelligent Analysis for Personality Detection on Various Indicators by Clinical Reliable Psychological TTH and stress Surveys;automatic Multilingual System from Speech;an Improved Data Hiding Scheme Through Image Interpolation;generalization of Multi-bit Encoding Function Based Data Hiding Scheme;a Machine Learning Approach to Comment Toxicity Classification;a Minutia Detection Approach from Direct Gray-Scale Fingerprint Image Using Hit-or-Miss Transformation;face Identification via strategic Combination of Local Features;a study on Reversible Image Watermarking Using Xilinx System Generator;a Novel Enhancement and Segmentation of Color Retinal Image Based on Fuzzy Measure and Fuzzy Integral;SVM and MLP Based Segmentation and recognition of Text from Scene Images Through an Effective Binarization Scheme;user Identification and Authentication Through Voice Samples;template Matching for Kinship Verification in the Wild;Attack Prevention Scheme for Privacy Preservation (APSP) Using K Anonymity in Location Based Services for IoT;statistical Analysis of the UNSW-NB15 Dataset for Intrusion Detection;Singer Identification Using MFCC and CRP Features with Support Vector Machines;object Proposals Based on Variance Measure;deep Learning Approach in Predicting Personal Traits Based on the Way User Type on Touchscreen;Robust Non-blind Video Watermarking Using DWT and QR Decomposition;detection and Classification of Earthquake Images from Online Social Media;On the Cryptanalysis of S-DES Using Binary Cuckoo Search Algorithm;numerical Integration Based Contrast Enhancement Using Simpson’s Method;self Driving Car.

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Applications of computational intelligence Techniques for Automatic Generation Control Problem—A Short Review from 2010 to 2018 1st

Applications of Computational Intelligence Techniques for Au...

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

作者： Gorripotu, Tulasichandra Sekhar Gopi, Simma Samalla, Halini Prasanna, A.V.L. Samira, B. Department of Electrical & Electronics Engineering Sri Sivani College of Engineering SrikakulamAndhra Pradesh532410 India

ISBN: (纸本)9789811390418

This work provides a brief review report on applications of computational intelligence techniques for automatic generation control (AGC) problem. Various optimization techniques employed to the conventional multi-area power system and restructured power system are highlighted. With that, the review also highlights the types of controllers used for various types of systems. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Controllers

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Blood Vessel Extraction from Retinal Images Using Modified Gaussian Filter and Bottom-Hat Transformation 1st

Blood Vessel Extraction from Retinal Images Using Modified G...

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

作者： Halder, Amiya Ghose, Sneha Department of CSE St. Thomas’ College of Engineering and Technology 4 D. H. Road Kidderpore Kolkata700023 India

ISBN: (纸本)9789811390418

Extraction of Retinal blood vessels are important for computer-aided diagnosis of ophthalmologic diseases. This paper presents a novel method for the detection of blood vessels of the retina. In proposed algorithm, at first, the background of the retinal vessels is removed. Then we perform modified Gaussian filtering to remove the noise of the image. The resulting image is subjected to Bottom-hat transformation and thereafter a width-dependant threshold operation is carried out to extract the blood vessels effectively. The proposed method is very efficient and less computational time as compared to the previously implemented methods and is thus very useful. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Blood vessels

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Particle Swarm-Based Approach for storage Efficiency Optimization of Supercapacitors 1st

Particle Swarm-Based Approach for Storage Efficiency Optimiz...

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

作者： Mahindar, Rudrendu Mukherjee, Sahana Dutta, Sankhadeep Dutta, Tanusree Ghosh, Rabindranath Electronics and Communication Engineering Department St. Thomas’ College of Engineering and Technology Kolkata700023 India

ISBN: (纸本)9789811390418

In the recent years, with the advent of artificial intelligence in multidisciplinary fields, more and more efficient mechanisms, to enhance the performance of various systems, are gaining prominence. This paper exploits the technique of computational intelligence to optimize the storage efficiency of supercapacitors. While a supercapacitor is a high-value capacitor, it can be used as an energy storage device like batteries. The storage efficiency of a supercapacitor depends directly on the capacitance value and inversely on the Equivalent Series Resistance (ESR) value. Supercapacitors with high storage efficiency can be deployed in numerous applications requiring high power-handling capacity. Different optimization methods have been used to maximize the storage efficiency of supercapacitors. In this paper, Particle Swarm Optimization (PSO) technique has been used in which the values of storage efficiency obtained are higher than those from other conventional algorithms. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Capacitance

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Real-time Driving pattern Prediction Based on KPCA and Neural Network 1

Real-time Driving Pattern Prediction Based on KPCA and Neura...

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1st international conference on Industrial Artificial intelligence (IAI)

作者： Xie, Liang Tao, Jili Zhejiang Univ Coll Control Sci & Engn Hangzhou Peoples R China Zhejiang Univ Ningbo Inst Technol Ningbo Peoples R China

ISBN: (纸本)9781728135939

The approach of real-time driving pattern recognition based on Kernel Principle Component Analysis (KPCA) and Neural Network is put forward on uncertain driving conditions. Firstly, the dimension of vehicle driving patterns is reduced by KPCA. Then, the acquired low dimensional features are selected as the input of Neural Network for driving pattern classification. The simulation results show that KPCA + Neural Network has an advantage of nonlinear characteristics handling, which makes up for the limit of dealing with linear data by Principle Component Analysis (PCA). Moreover, Simulation results show that the dimension reduction of input patterns has simplified the structure of Neural Network by decreasing the number of hidden neurons greatly, and enhanced its real time recognition capability for driving patterns. The recognition accuracy reaches 95.24 percent.

关键词： kernel principle component analysis neural network uncertain driving condition driving pattern prediction

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Complete statistical Analysis to Weather Forecasting 1st

Complete Statistical Analysis to Weather Forecasting

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

作者： Datta, Anisha Si, Shukrity Biswas, Sanket Department of Computer Science and Engineering Jalpaiguri Government Engineering College Jalpaiguri735102 India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata700108 India

ISBN: (纸本)9789811390418

The primary objective of the model applied in this work is to predict the weather of a city named Austin in Texas using supervised machine learning algorithms. In this case, artificial neural networks and gradient boosting classifier were implemented to build models to predict weather and comparisons between these two models are also made for this dataset. Here, average temperature, average dew point, average pressure of sea level, average percentage of humidity, etc. are the parameters taken into consideration which influence the weather of the place. Using these parameters, the trained models performed a classification to predict whether the weather is rainy (thunderstorm or not), not rainy, snowy, or foggy. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Supervised learning

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Automatic Multilingual System from Speech 1st

Automatic Multilingual System from Speech

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

作者： Agarwal, Suchit Chatterjee, Akshay Yasmin, Ghazaala Department of Computer Science and Engineering St Thomas’ College of Engineering and Technology Kolkata700023 India

ISBN: (纸本)9789811390418

Language recognition is the way by which the language of a digital speech utterance is recognized automatically by a computer. Commenced Language Identification Systems sequentially transform the speech signal into discrete units, and then apply statistical methods on the resultant units to extract their language information. Today, a large number of audio retrieval features exists for automatic speech and language recognition. The proposed method has nominated an automatic system for well-known multi-languages. The identification has been done using a new set of audio features. The suitable feature has been adopted. This includes Zero-Crossing Rate, Spectral Flux, Pitch, Mel-frequency Cepstral Coefficients, Tempo, and Short-Time Energy. These features have been used exclusively for identifying the language along with the help of classifiers and feature selection algorithms. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Continuous speech recognition

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Weighted local directional pattern for robust facial expression recognition

Weighted local directional pattern for robust facial express...

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

作者： Rahman, Arifur Ali, Liakot IICT BUET Dhaka Bangladesh

ISBN: (纸本)9780769546186

A novel low-cost highly discriminatory feature space is introduced for facial expression recognition, which incorporates a weight to the Local Direction pattern (LDP), capable of robust performance over a range of image resolutions. In addition, we use Adaboost to pick a small set of high-flying features, which are used by the Support Vector Machine (SVM) to classify facial expressions proficiently. Experimental results show that the proposed technique improves both the accuracy and the speed of the final classifier compares to other existing state-of-the-art methods. © 2011 IEEE.

关键词： Support vector machines

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SVM and MLP Based Segmentation and recognition of Text from Scene Images Through an Effective Binarization Scheme 1st

SVM and MLP Based Segmentation and Recognition of Text from ...

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

作者： Ghoshal, Ranjit Banerjee, Ayan St. Thomas’ College of Engineering and Technology Kolkata700023 India Lexmark Research & Development Corporation Kolkata India

ISBN: (纸本)9789811390418

Text Binarization from scene images plays a crucial task for any text segmentation scheme and therefore in the OCR performance. So, an effective image binarization method is required for text segmentation and recognition tasks. This work describes an effective image binarization scheme for segmentation and recognition task of text from images. To binarize the image, Canny’s edge information is incorporated into Otsu’s method. It generates numerous components which are analyzed for segmentation of probable text components. Further, a few features are considered for classification of text and non-text. For this problem, SVM is considered. For training SVM classifier, information from ground-truth images of text and our own made non-text components are used. Finally, Multilayer Perceptron (MLP) is used for recognition of the text symbols. The MLP classifier is trained using 13496 samples of 39 classes. We tested our schemes on the publicly available ICDAR Born Digital data set. The outcomes are quite acceptable. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Binary images

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On the Synthesis of Unate Symmetric Function Using Memristor-Based Nano-Crossbar Circuit 1st

On the Synthesis of Unate Symmetric Function Using Memristor...

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

作者： Basu, Subhashree Kule, Malay ST. Thomas’ College of Engineering and Technology Kolkata India Indian Institute of Engineering Science and Technology ShibpurHowrah India

ISBN: (纸本)9789811390418

VLSI technology can integrate a large number of electronic components into a single chip. But as per the Moore’s prediction, this technology will soon hit a wall and no further miniaturization of VLSI chips will be possible. Because of this blockade that the technology would soon face, the scientists are turning their focus to emerging nanotechnology. Memristor can be such an alternative, which has the potential of very high speed, smaller size, and minimum power consumption compared to transistor-based technology. Memristor can be considered synonymous to "memory plus resistor" where its internal resistance acts as the data value stored in it, and it has the capability of retaining its previous resistance value even when the power supply is withdrawn. This paper utilizes this unique property of memristor in a new way to simulate unate symmetric functions. Implementation of 3- and 5-input unate symmetric functions are shown in the memristor-based memristor circuit. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Nanotechnology

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