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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21-30 订阅

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Detection and Classification of Earthquake Images from Online Social Media 1st

Detection and Classification of Earthquake Images from Onlin...

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

作者： Layek, Ashish Kumar Chatterjee, Amreeta Chatterjee, Debanjan Biswas, Samit Indian Institute of Engineering Science and Technology Shibpur711103 India St. Thomas’ College of Engineering & Technology Kolkata700023 India

ISBN: (纸本)9789811390418

Natural disasters present a huge challenge for Government and non-Governmental organizations, as the individuals and communities are heavily affected. Disasters like earthquakes are seismic events that result in shaking of the earth’s surface causing large-scale death and destruction. Therefore, disaster management and control are of utmost importance. Nowadays individuals on site use social media platforms (like Twitter, Facebook, etc.) for sharing information and seeking remedy. If the extent of destruction can be estimated, one can assess the amount of relief needed. Thus, the data gathered from social media platforms can be used to evaluate the extremity of architectural damage induced by disasters like earthquakes. This paper proposes a CNN based segmentation of earthquake affected regions in images that are posted on online social media and classifying them into various classes according to the severity of damage. The approach is trained and tested using a dataset of images collected from social media posts during earthquakes and the results are encouraging. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Earthquakes

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Proceedings - 2017 5th international conference on Applied Computing and Information Technology, 2017 4th international conference on computational Science/intelligence and Applied Informatics and 2017 1st international conference on Big Data, Cloud Computing, Data Science and Engineering, ACIT-CSII-BCD 2017

Proceedings - 2017 5th International Conference on Applied C...

引用

5th international conference on Applied Computing and Information Technology, 2017 4th international conference on computational Science/intelligence and Applied Informatics and 2017 1st international conference on Big Data, Cloud Computing, Data Science and Engineering, ACIT-CSII-BCD 2017

ISBN: (纸本)9781538633021

The proceedings contain 44 papers. The topics discussed include: a learning material for physics experiment with high-accuracy using computer vision technique;automatic classification of remarks in werewolf BBS;a rapid incremental frequent pattern mining algorithm for uncertain data;global and local bursts detection in streaming data;two-mode three-way dominance points model for periodic dissimilarity;an intelligent noninvasive taste detection app for watermelons;automated risk identification of CMMI project planning using ontology;and depth recognition in 3D translucent stereoscopic imaging of medical volumes by means of a glasses-free 3d display.

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Classification of Speech and Song Using Co-occurrence-Based Approach 1st

Classification of Speech and Song Using Co-occurrence-Based ...

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

作者： Ghosal, Arijit Dutta, Suchibrota Banerjee, Debanjan Department of Information Technology St. Thomas’ College of Engineering and Technology KolkataWest Bengal700023 India Department of Information Technology and Mathematics Royal Thimphu College Thimphu Bhutan Department of MIS Sarva Siksha Mission Kolkata KolkataWest Bengal700042 India

ISBN: (纸本)9789811390418

Discriminating song and speech from audio is an exigent problem. This is a step toward self-executing categorization in case of audio signal. Foregoing attempts were mostly involved for discriminating speech with nonspeech but relatively not much works were involved for classifying speech and song from audio signal. Mainly perceptual and frequency depended features were associated with the foregoing attempts. Song, whether it is associated with instrument or not, reveals some type of periodicity, whereas this periodicity is absent in case of normal speech. For accurate study of these periodic nature textural features based on its co-occurrence matrix along with its mean and standard deviation are also considered. Support Vector Machine (SVM), Neural Network (NN), and k-Nearest Neighbor (k-NN) have been brought into play for the purpose of taxonomy of speech from song. Speech and song classification precision obtained in this work has been compared with that of some other previous works done to reveal effectiveness of the advised feature set. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Speech

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New approaches of radial basis function network for pattern classifiers

New approaches of radial basis function network for pattern ...

引用

4th international conference on Computer Science and Informatics, JCIS 1998, 1st international Workshop on High Performance, 1st international Workshop on Computer Vision, pattern recognition and Image Processing Volume 4

作者： Baghavan, S. Li, R. Lebby, G. Sherrod, E. NASA ACE Center Dept. of Electrical Engineering N.C. A and T State University Greensboro NC 27411

The application of neural network technology for pattern recognition and classification in the field of machine intelligence requires advanced computational procedures. Radial Basis Function Networks (RBFN) have been getting more attention recently in neural network design for classification purpose. We have devised a procedure to determine the optimal spread of the radial basis functions for performance improvement. We are comparing the results of the radial basis function approach with those of the backpropagation approach for performances on speed and generalization.

关键词： Radial basis function networks

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Proceedings of 2021 1st international conference on Computer Science and Artificial intelligence, ICCSAI 2021

Proceedings of 2021 1st International Conference on Computer...

引用

1st international conference on Computer Science and Artificial intelligence, ICCSAI 2021

ISBN: (纸本)9781728133331

The proceedings contain 81 papers. The topics discussed include: adaptive central pattern generators to control human/robot interactions;modelling personality prediction from user's posting on social media;web based application for ordering food raw materials;comparison of Gaussian hidden Markov model and convolutional neural network in sign language recognition system;intelligent computational model for early heart disease prediction using logistic regression and stochastic gradient descent (a preliminary study);an efficient system to collect data for ai training on multi-category object counting task;a comparison of artificial intelligence-based methods in traffic prediction;impact of computer vision with deep learning approach in medical imaging diagnosis;and development of portable temperature and air quality detector for preventing COVID-19.

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Robust face recognition using wavelet and dct based lighting normalization, and shifting-mean lda

Robust face recognition using wavelet and dct based lighting...

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

作者： Gede Pasek Suta Wijaya, I. Uchimura, Keiichi Koutaki, Gou Zhang, Cuicui Electrical Engineering and Computer Science Dept. Kumamoto University Kurokami 2-39-1 Kumamoto Shi Japan Electrical Engineering Dept. Mataram University Jl. Majapahit 62 Mataram Indonesia Department of Intelligence Science and Technology Graduate School of Informatics Kyoto University Kyoto Japan

ISBN: (纸本)9789898425980

This paper presents an integration of Wavelet and Discrete Cosine Transform (DCT) based lighting normalization, and shifting-mean Linear Discriminant Analysis (LDA) based face classifiers for face recognition. The aims are to provide robust recognition rate against large face variability due to lighting variations and to avoid retraining problem of the classical LDA for incremental data. In addition, the compact holistic features is employed for dimensional reduction of the raw face image. From the experimental results, the proposed method gives sufficient and robust achievement in terms of recognition rate and requires short computational time.

关键词： Lighting

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A MULTI-VALUED NEURON WITH A PERIODIC ACTIVATION FUNCTION

A MULTI-VALUED NEURON WITH A PERIODIC ACTIVATION FUNCTION

引用

1st international Joint conference on computational intelligence

作者： Aizenberg, Igor Texas A&M Univ Texarkana Dept Comp Sci Texarkana TX 75505 USA

ISBN: (纸本)9789896740146

In this paper, a new activation function for the multi-valued neuron (MVN) is presented. The MVN is a neuron with complex-valued weights and inputs/output, which are located on the unit circle. Although the MVN has a greater functionality than a sigmoidal or radial basis function neurons, it has a limited capability of learning highly nonlinear functions. A periodic activation function, which is introduced in this paper, makes it possible to learn nonlinearly separable problems and non-threshold multiple-valued functions using a single multi-valued neuron. The MVN's functionality becomes higher and the MVN becomes more efficient in solving various classification problems. A learning algorithm based on the error-correction rule for an MVN with the introduced activation function is also presented.

关键词： Complex-valued neural networks Derivative-free learning pattern recognition Classification

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Needle segmentation using 3D quick randomized hough transform

Needle segmentation using 3D quick randomized hough transfor...

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1st international conference on Intelligent Networks and Intelligent Systems, ICINIS 2008

作者： Qiu, Wu Ding, Mingyue Yuchi, Ming Institute for Pattern Recognition and Artificial Intelligence Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan Hubei China Department of Biomedical Engineering School of Life Science and Technology Huazhong University of Science and Technology Wuhan Hubei China

ISBN: (纸本)9780769533919

A quick 3D needle segmentation algorithm for 3D US data is described in this paper. The algorithm includes the 3D Quick Randomized Hough Transform (3DGHT), which is based on the 3D Randomized Hough Transform and coarse-fine searching strategy. We tested it with water phantom. The results show that our algorithm works well in 3D US images with angular deviation less than 1 and position deviation less than 1mm, and the computational time of segmentation with 35MB data is within 1s. © 2008 IEEE.

关键词： Hough transforms

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Application of Pseudo 2-D Hidden Markov Model for Hand Gesture recognition 1st

Application of Pseudo 2-D Hidden Markov Model for Hand Gestu...

引用

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

作者： Sagayam, K. Martin Hemanth, D. Jude Karunya Univ Dept ECE Coimbatore Tamil Nadu India

ISBN: (纸本)9789811024719;9789811024702

Hand gesture recognition is the temporal pattern analysis with mathematical interpretation. It provides the means for the non-verbal communication among the people, more natural and powerful means of human-computer interaction (HCI) for the virtual reality application. The development of human-computer stochastic processes has led to a 1-D hidden Markov models (1DHMMs) and training algorithms to find the high recognition rate and low computational complexity. Due to their dimensionality and computational efficiency, Pseudo 2-D HMMs (P2DHMMs) are often favored for a flexible way of presenting events with temporal and dynamic variations. Both 1-D HMM and 2-D HMM are present in hand gestures, which are of increasing interest in the research of hand gesture recognition (HGR). The main issue of 1-D HMM is the fact that the recursiveness in the forward and backward procedures typically multiply probability values between themselves. Hence, this product quickly tends to zero and goes beyond any machine storage capabilities. This work presents an application of Pseudo 2-D HMM to classify the hand gestures from measured values of an accelerating image. Comparing an experimental result between 1-D HMM and Pseudo 2-D HMM with respect to recognition rate and accuracy, it shows a prominent result for the proposed approach.

关键词： Human-computer interface 1-D HMM Pseudo 2-D HMM HGR

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Systematically evolving configuration parameters for computational intelligence methods

引用

1st international conference on pattern recognition and Machine intelligence, PReMI 2005

作者： Proctor, Jason M. Weber, Rosina College of Information Science and Technology Drexel University

ISBN: (纸本)3540305068

The configuration of a computational intelligence (CI) method is responsible for its intelligence (e.g. tolerance, flexibility) as well as its accuracy. In this paper, we investigate how to automatically improve the performance of a CI method by finding alternate configuration parameter values that produce more accurate results. We explore this by using a genetic algorithm (GA) to find suitable configurations for the CI methods in an integrated CI system, given several different input data sets. This paper describes the implementation and validation of our approach in the domain of software testing, but ultimately we believe it can be applied in many situations where a CI method must produce accurate results for a wide variety of problems. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Artificial intelligence

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