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Infrared Spectral Classification With Artificial Neural Networks And Classical Pattern Recognition
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Book Synopsis Infrared Spectral Classification with Artificial Neural Networks and Classical Pattern Recognition by :
Download or read book Infrared Spectral Classification with Artificial Neural Networks and Classical Pattern Recognition written by and published by . This book was released on 2000 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt: Infrared spectroscopy is an important technique for measuring airborne chemicals, for pollution monitoring and to warn of toxic compound releases. Infrared spectroscopy provides both detection and identification of airborne components. Computer-assisted classification tools, including pattern recognition and artificial neural network techniques, have been applied to a collection of infrared spectra of organophosphorus compounds, and these have successfully discriminated commercial pesticide compounds from military nerve agents, precursors, and hydrolysis products. Infrared spectra for previous tests came from a commercial infrared library, with permission, from military laboratories, and from defense contractors. In order to further test such classification tools, additional infrared spectra from the NIST gas-phase infrared library were added to the data set. These additional spectra probed the tendency of the trained classifiers to misidentify unrelated spectra into the trained classes. Infrared spectra used in this effort were gathered from a variety of sources. Different instrument operators collected them at a number of locations, in a variety of spectral data collection designs, and they were delivered in a variety of digital formats. The spectra were treated mathematically to remove artifacts from their collection. Preprocessing techniques used included Fisher weighting and principal component analysis. Classifications were made using the k-nearest neighbor classifier, feed forward neural networks, trained with a variety of techniques, and radial basis function networks. The results from these classification techniques will be reported and compared.
Book Synopsis Chemical and Biological Sensing by :
Download or read book Chemical and Biological Sensing written by and published by . This book was released on 2000 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Stellar Spectral Classification by : Richard O. Gray
Download or read book Stellar Spectral Classification written by Richard O. Gray and published by Princeton University Press. This book was released on 2021-06-08 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by leading experts in the field, Stellar Spectral Classification is the only book to comprehensively discuss both the foundations and most up-to-date techniques of MK and other spectral classification systems. Definitive and encyclopedic, the book introduces the astrophysics of spectroscopy, reviews the entire field of stellar astronomy, and shows how the well-tested methods of spectral classification are a powerful discovery tool for graduate students and researchers working in astronomy and astrophysics. The book begins with a historical survey, followed by chapters discussing the entire range of stellar phenomena, from brown dwarfs to supernovae. The authors account for advances in the field, including the addition of the L and T dwarf classes; the revision of the carbon star, Wolf-Rayet, and white dwarf classification schemes; and the application of neural nets to spectral classification. Copious figures illustrate the morphology of stellar spectra, and the book incorporates recent discoveries from earth-based and satellite data. Many examples of spectra are given in the red, ultraviolet, and infrared regions, as well as in the traditional blue-violet optical region, all of which are useful for researchers identifying stellar and galactic spectra. This essential reference includes a glossary, handy appendixes and tables, an index, and a Web-based resource of spectra. In addition to the authors, the contributors are Adam J. Burgasser, Margaret M. Hanson, J. Davy Kirkpatrick, and Nolan R. Walborn.
Book Synopsis Pattern Recognition and Classification of Vibrational Spectra by Artificial Neural Networks by : Husheng Yang
Download or read book Pattern Recognition and Classification of Vibrational Spectra by Artificial Neural Networks written by Husheng Yang and published by . This book was released on 1999 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Pattern Recognition by : Sankar K. Pal
Download or read book Pattern Recognition written by Sankar K. Pal and published by World Scientific. This book was released on 2001 with total page 644 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume, containing contributions by experts from all over the world, is a collection of 21 articles which present review and research material describing the evolution and recent developments of various pattern recognition methodologies, ranging from statistical, syntactic/linguistic, fuzzy-set-theoretic, neural, genetic-algorithmic and rough-set-theoretic to hybrid soft computing, with significant real-life applications. In addition, the book describes efficient soft machine learning algorithms for data mining and knowledge discovery. With a balanced mixture of theory, algorithms and applications, as well as up-to-date information and an extensive bibliography, Pattern Recognition: From Classical to Modern Approaches is a very useful resource. Contents: Pattern Recognition: Evolution of Methodologies and Data Mining (A Pal & S K Pal); Adaptive Stochastic Algorithms for Pattern Classification (M A L Thathachar & P S Sastry); Shape in Images (K V Mardia); Decision Trees for Classification: A Review and Some New Results (R Kothari & M Dong); Syntactic Pattern Recognition (A K Majumder & A K Ray); Fuzzy Sets as a Logic Canvas for Pattern Recognition (W Pedrycz & N Pizzi); Neural Network Based Pattern Recognition (V David Sanchez A); Networks of Spiking Neurons in Data Mining (K Cios & D M Sala); Genetic Algorithms, Pattern Classification and Neural Networks Design (S Bandyopadhyay et al.); Rough Sets in Pattern Recognition (A Skowron & R Swiniarski); Automated Generation of Qualitative Representations of Complex Objects by Hybrid Soft-Computing Methods (E H Ruspini & I S Zwir); Writing Speed and Writing Sequence Invariant On-line Handwriting Recognition (S-H Cha & S N Srihari); Tongue Diagnosis Based on Biometric Pattern Recognition Technology (K Wang et al.); and other papers. Readership: Graduate students, researchers and academics in pattern recognition.
Book Synopsis Interpretation and Identification of Infrared and Mass Spectra with Neural Networks by : Christoph Klawun
Download or read book Interpretation and Identification of Infrared and Mass Spectra with Neural Networks written by Christoph Klawun and published by . This book was released on 1995 with total page 588 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :Khalid J. Siddiqui Publisher :SPIE-International Society for Optical Engineering ISBN 13 : Total Pages :158 pages Book Rating :4.3/5 (91 download)
Book Synopsis Pattern Recognition, Chemometrics, and Imaging for Optical Environmental Monitoring by : Khalid J. Siddiqui
Download or read book Pattern Recognition, Chemometrics, and Imaging for Optical Environmental Monitoring written by Khalid J. Siddiqui and published by SPIE-International Society for Optical Engineering. This book was released on 1999 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work presents a selection of papers dealing with various aspects of pattern recognition, chemometrics and imaging for optical environment monitoring.
Book Synopsis Hyperspectral Image Analysis by : Saurabh Prasad
Download or read book Hyperspectral Image Analysis written by Saurabh Prasad and published by Springer Nature. This book was released on 2020-04-27 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks, with a focus on emerging trends in machine learning and image processing/understanding. It presents advances in deep learning, multiple instance learning, sparse representation based learning, low-dimensional manifold models, anomalous change detection, target recognition, sensor fusion and super-resolution for robust multispectral and hyperspectral image understanding. It presents research from leading international experts who have made foundational contributions in these areas. The book covers a diverse array of applications of multispectral/hyperspectral imagery in the context of these algorithms, including remote sensing, face recognition and biomedicine. This book would be particularly beneficial to graduate students and researchers who are taking advanced courses in (or are working in) the areas of image analysis, machine learning and remote sensing with multi-channel optical imagery. Researchers and professionals in academia and industry working in areas such as electrical engineering, civil and environmental engineering, geosciences and biomedical image processing, who work with multi-channel optical data will find this book useful.
Book Synopsis Classification of Infrared Spectra of Organophosphorus Compounds with Artificial Neural Networks by :
Download or read book Classification of Infrared Spectra of Organophosphorus Compounds with Artificial Neural Networks written by and published by . This book was released on 1999 with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt: AERL/AFIT examined the use of artificial neural networks to classify infrared spectra of organophosphorus pesticides and chemically related compounds. The spectra used were contributed from commercial libraries, government agencies, and government contractors and include spectra of pesticides, industrial precursers, hydrolysis products and other organophosphorus compounds. The data were pretreated to reduce artifacts arising from the variety of collection sources. The treated spectra were divided into spectral "bins" of equal frequency width and transduced into data vectors whose elements consisted of the average absorbance value of the corresponding spectral bin. The spectral data vectors served as inputs to neural networks examined as spectral classifiers. Conventional feed-forward neural networks were constructed using the spectral data vectors as inputs and indicating the chemical class in the output nodes. Several training methods were compared for efficiency in setting the network weights and biases, from the standpoint of time needed to train the network and from the error frequencies obtained. Network architecture was also examined in order to obtain the optimum number of nodes to place in the hidden layers of the networks. Radial basis function networks were also generated from spectral input data and used to classify the spectra. The final classification accuracies and training efficiencies from these networks were compared with those from the feed forward networks. The radial basis function networks could be trained rapidly and produced numerically stable networks, but the network generation technique tended to produce large numbers of hidden nodes. The radial basis function networks gave the best classification accuracy obtained with neural network classifiers.
Book Synopsis Statistical Treatment of Analytical Data by : Zeev B. Alfassi
Download or read book Statistical Treatment of Analytical Data written by Zeev B. Alfassi and published by John Wiley & Sons. This book was released on 2009-02-12 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical techniques have assumed an integral role in both the interpretation and quality assessment of analytical results. In this book the range of statistical methods available for such tasks are described in detail, with the advantages and disadvantages of each technique clarified by use of examples. With a focus on the essential practical application of these techniques the book also includes sufficient theory to facilitate understanding of the statistical principles involved. Statistical Treatment of Analytical Data is written for professional analytical chemists in industry, government and research institutions who require a practical understanding of the application of statistics in day to day activities in the analytical laboratory. It is also for students who require further and detailed information that may not be available directly in a typical undergraduate course.
Book Synopsis Infrared Spectroscopy by : Marwa El-Azazy
Download or read book Infrared Spectroscopy written by Marwa El-Azazy and published by BoD – Books on Demand. This book was released on 2019-03-06 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: Delving into Infrared Spectroscopy: Principles, Advances and Applications, and with basic knowledge of IR spectroscopy, will provide the reader with a synopsis of fundamentals and groundbreaking advances in the field. Readers will see a variety of MIR applications and difficulties encountered, especially in an industrial environment. Competency in FT-IR spectroscopy in biomedical research and early-stage diagnosis of obesity is shown. Challenges associated with VIS-NIR applications are shown through application of the technique in assessing quality parameters of fruits. Moreover, IR spectroscopic studies of radiation-stimulated processes, and the influence of using IR in developing an ideal catalyst and hence an efficient catalysis process, are discussed. The impact of coupling multivariate data analysis techniques to IR is shown in almost every chapter.
Book Synopsis Recognition of Visual Characteristics of Infrared Spectra by Artificial Neural Networks and Partial Least Squares Regression by : Tom Visser
Download or read book Recognition of Visual Characteristics of Infrared Spectra by Artificial Neural Networks and Partial Least Squares Regression written by Tom Visser and published by . This book was released on 1993 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Image Analysis and Processing - ICIAP 2017 by : Sebastiano Battiato
Download or read book Image Analysis and Processing - ICIAP 2017 written by Sebastiano Battiato and published by Springer. This book was released on 2017-10-11 with total page 788 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNCS 10484 and 10485 constitutes the refereed proceedings of the 19th International Conference on Image Analysis and Processing, ICIAP 2017, held in Catania, Italy, in September 2017. The 138 papers presented were carefully reviewed and selected from 229 submissions. The papers cover both classic and the most recent trends in image processing, computer vision, and pattern recognition, addressing both theoretical and applicative aspects. They are organized in the following topical sections: video analysis and understanding; pattern recognition and machine learning; multiview geometry and 3D computer vision; image analysis, detection and recognition; multimedia; biomedical and assistive technology; information forensics and security; imaging for cultural heritage and archaeology; and imaging solutions for improving the quality of life.
Book Synopsis Supervised and Unsupervised Pattern Recognition by : Evangelia Miche Tzanakou
Download or read book Supervised and Unsupervised Pattern Recognition written by Evangelia Miche Tzanakou and published by CRC Press. This book was released on 2017-12-19 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: There are many books on neural networks, some of which cover computational intelligence, but none that incorporate both feature extraction and computational intelligence, as Supervised and Unsupervised Pattern Recognition does. This volume describes the application of a novel, unsupervised pattern recognition scheme to the classification of various types of waveforms and images. This substantial collection of recent research begins with an introduction to Neural Networks, classifiers, and feature extraction methods. It then addresses unsupervised and fuzzy neural networks and their applications to handwritten character recognition and recognition of normal and abnormal visual evoked potentials. The third section deals with advanced neural network architectures-including modular design-and their applications to medicine and three-dimensional NN architecture simulating brain functions. The final section discusses general applications and simulations, such as the establishment of a brain-computer link, speaker identification, and face recognition. In the quickly changing field of computational intelligence, every discovery is significant. Supervised and Unsupervised Pattern Recognition gives you access to many notable findings in one convenient volume.
Book Synopsis Computational Intelligence for Pattern Recognition by : Witold Pedrycz
Download or read book Computational Intelligence for Pattern Recognition written by Witold Pedrycz and published by Springer. This book was released on 2018-04-30 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents a comprehensive and up-to-date review of fuzzy pattern recognition. It carefully discusses a range of methodological and algorithmic issues, as well as implementations and case studies, and identifies the best design practices, assesses business models and practices of pattern recognition in real-world applications in industry, health care, administration, and business. Since the inception of fuzzy sets, fuzzy pattern recognition with its methodology, algorithms, and applications, has offered new insights into the principles and practice of pattern classification. Computational intelligence (CI) establishes a comprehensive framework aimed at fostering the paradigm of pattern recognition. The collection of contributions included in this book offers a representative overview of the advances in the area, with timely, in-depth and comprehensive material on the conceptually appealing and practically sound methodology and practices of CI-based pattern recognition.
Book Synopsis Scientific and Technical Aerospace Reports by :
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1995 with total page 994 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Pattern Recognition Program for the Identification of Infrared Spectra by : David Grant Hurrell
Download or read book Pattern Recognition Program for the Identification of Infrared Spectra written by David Grant Hurrell and published by . This book was released on 1985 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt:
