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Improving Classifier Generalization
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Book Synopsis Improving Classifier Generalization by : Rahul Kumar Sevakula
Download or read book Improving Classifier Generalization written by Rahul Kumar Sevakula and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book elaborately discusses techniques commonly used to improve generalization performance in classification approaches. The contents highlight methods to improve classification performance in numerous case studies: ranging from datasets of UCI repository to predictive maintenance problems and cancer classification problems. The book specifically provides a detailed tutorial on how to approach time-series classification problems and discusses two real time case studies on condition monitoring. In addition to describing the various aspects a data scientist must consider before finalizing their approach to a classification problem and reviewing the state of the art for improving classification generalization performance, it also discusses in detail the authors own contributions to the field, including MVPC - a classifier with very low VC dimension, a graphical indices based framework for reliable predictive maintenance and a novel general-purpose membership functions for Fuzzy Support Vector Machine which provides state of the art performance with noisy datasets, and a novel scheme to introduce deep learning in Fuzzy Rule based classifiers (FRCs). This volume will serve as a useful reference for researchers and students working on machine learning, health monitoring, predictive maintenance, time-series analysis, gene-expression data classification. .
Book Synopsis Improving Classifier Generalization by : Rahul Kumar Sevakula
Download or read book Improving Classifier Generalization written by Rahul Kumar Sevakula and published by Springer Nature. This book was released on 2022-09-29 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book elaborately discusses techniques commonly used to improve generalization performance in classification approaches. The contents highlight methods to improve classification performance in numerous case studies: ranging from datasets of UCI repository to predictive maintenance problems and cancer classification problems. The book specifically provides a detailed tutorial on how to approach time-series classification problems and discusses two real time case studies on condition monitoring. In addition to describing the various aspects a data scientist must consider before finalizing their approach to a classification problem and reviewing the state of the art for improving classification generalization performance, it also discusses in detail the authors own contributions to the field, including MVPC - a classifier with very low VC dimension, a graphical indices based framework for reliable predictive maintenance and a novel general-purpose membership functions for Fuzzy Support Vector Machine which provides state of the art performance with noisy datasets, and a novel scheme to introduce deep learning in Fuzzy Rule based classifiers (FRCs). This volume will serve as a useful reference for researchers and students working on machine learning, health monitoring, predictive maintenance, time-series analysis, gene-expression data classification.
Book Synopsis Improving the Generalization Ability of Neural Network Classifiers by : Kailash L. Kalantri
Download or read book Improving the Generalization Ability of Neural Network Classifiers written by Kailash L. Kalantri and published by . This book was released on 1992 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Generalization With Deep Learning: For Improvement On Sensing Capability by : Zhenghua Chen
Download or read book Generalization With Deep Learning: For Improvement On Sensing Capability written by Zhenghua Chen and published by World Scientific. This book was released on 2021-04-07 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning has achieved great success in many challenging research areas, such as image recognition and natural language processing. The key merit of deep learning is to automatically learn good feature representation from massive data conceptually. In this book, we will show that the deep learning technology can be a very good candidate for improving sensing capabilities.In this edited volume, we aim to narrow the gap between humans and machines by showcasing various deep learning applications in the area of sensing. The book will cover the fundamentals of deep learning techniques and their applications in real-world problems including activity sensing, remote sensing and medical sensing. It will demonstrate how different deep learning techniques help to improve the sensing capabilities and enable scientists and practitioners to make insightful observations and generate invaluable discoveries from different types of data.
Book Synopsis Wireless Networks and Computational Intelligence by : K. R. Venugopal
Download or read book Wireless Networks and Computational Intelligence written by K. R. Venugopal and published by Springer. This book was released on 2012-07-11 with total page 671 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 6th International Conference on Information Processing, ICIP 2012, held in Bangalore, India, in August 2012. The 75 revised full papers presented were carefully reviewed and selected from 380 submissions. The papers are organized in topical sections on wireless networks; image processing; pattern recognition and classification; computer architecture and distributed computing; software engineering, information technology and optimization techniques; data mining techniques; computer networks and network security.
Book Synopsis Computer Networks and Intelligent Computing by : K. R. Venugopal
Download or read book Computer Networks and Intelligent Computing written by K. R. Venugopal and published by Springer. This book was released on 2011-07-20 with total page 701 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 5th International Conference on Information Processing, ICIP 2011, held in Bangalore, India, in August 2011. The 86 revised full papers presented were carefully reviewed and selected from 514 submissions. The papers are organized in topical sections on data mining; Web mining; artificial intelligence; soft computing; software engineering; computer communication networks; wireless networks; distributed systems and storage networks; signal processing; image processing and pattern recognition.
Book Synopsis Harnessing Unlabeled Data for Improving Generalization of Deep Learning Methods by : Deepika Shanmugasundaram
Download or read book Harnessing Unlabeled Data for Improving Generalization of Deep Learning Methods written by Deepika Shanmugasundaram and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advancements in Deep Learning, Artificial Intelligence, and Computer Vision have reached a critical stage, enabling researchers to explore the automatic extraction of individual demographic traits, known as soft-biometrics. This research aims to leverage unlabeled data in predicting soft-biometric traits, such as gender and age, using deep learning models. The objective is to develop a model that can accurately classify these traits by utilizing semi-supervised methods that rely on a limited amount of labeled data and a vast amount of unlabeled data. While unlabeled data may initially seem devoid of crucial information, this thesis explores how it can be effectively used to enhance classification accuracy, especially in scenarios where labeled data is scarce. This study evaluated the accuracy of different image classification models on the Celeb-A and NIR-VIS datasets using co-training, mix-up procedure, knowledge distillation, and blind distillation techniques. The results showed that incorporating these methods led to improvements in accuracy across both datasets and various attributes such as gender classification and smiling classification. Exploring the combined use of different techniques and investigating their synergistic effects could lead to further accuracy improvements. Evaluating the models on larger and more diverse datasets, analyzing their generalization capabilities, optimizing hyperparameters and architectures, and applying the techniques to other computer vision tasks were also identified as areas for future research.
Book Synopsis Computational Science – ICCS 2021 by : Maciej Paszynski
Download or read book Computational Science – ICCS 2021 written by Maciej Paszynski and published by Springer Nature. This book was released on 2021-06-10 with total page 758 pages. Available in PDF, EPUB and Kindle. Book excerpt: The six-volume set LNCS 12742, 12743, 12744, 12745, 12746, and 12747 constitutes the proceedings of the 21st International Conference on Computational Science, ICCS 2021, held in Krakow, Poland, in June 2021.* The total of 260 full papers and 57 short papers presented in this book set were carefully reviewed and selected from 635 submissions. 48 full and 14 short papers were accepted to the main track from 156 submissions; 212 full and 43 short papers were accepted to the workshops/ thematic tracks from 479 submissions. The papers were organized in topical sections named: Part I: ICCS Main Track Part II: Advances in High-Performance Computational Earth Sciences: Applications and Frameworks; Applications of Computational Methods in Artificial Intelligence and Machine Learning; Artificial Intelligence and High-Performance Computing for Advanced Simulations; Biomedical and Bioinformatics Challenges for Computer Science Part III: Classifier Learning from Difficult Data; Computational Analysis of Complex Social Systems; Computational Collective Intelligence; Computational Health Part IV: Computational Methods for Emerging Problems in (dis-)Information Analysis; Computational Methods in Smart Agriculture; Computational Optimization, Modelling and Simulation; Computational Science in IoT and Smart Systems Part V: Computer Graphics, Image Processing and Artificial Intelligence; Data-Driven Computational Sciences; Machine Learning and Data Assimilation for Dynamical Systems; MeshFree Methods and Radial Basis Functions in Computational Sciences; Multiscale Modelling and Simulation Part VI: Quantum Computing Workshop; Simulations of Flow and Transport: Modeling, Algorithms and Computation; Smart Systems: Bringing Together Computer Vision, Sensor Networks and Machine Learning; Software Engineering for Computational Science; Solving Problems with Uncertainty; Teaching Computational Science; Uncertainty Quantification for Computational Models *The conference was held virtually.
Book Synopsis Information Processing in Medical Imaging by : Gábor Székely
Download or read book Information Processing in Medical Imaging written by Gábor Székely and published by Springer Science & Business Media. This book was released on 2011-06-29 with total page 806 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 22nd International Conference on Information Processing in Medical Imaging, IPMI 2011, held at Kloster Irsee, Germany, in July 2011. The 24 full papers and 39 poster papers included in this volume were carefully reviewed and selected from 224 submissions. The papers are organized in topical sections on segmentation, statistical methods, shape analysis, registration, diffusion imaging, disease progression modeling, and computer aided diagnosis. The poster sessions deal with segmentation, shape analysis, statistical methods, image reconstruction, microscopic image analysis, computer aided diagnosis, diffusion imaging, functional brain analysis, registration and other related topics.
Book Synopsis Machine Learning in Document Analysis and Recognition by : Simone Marinai
Download or read book Machine Learning in Document Analysis and Recognition written by Simone Marinai and published by Springer Science & Business Media. This book was released on 2008-01-10 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of Document Analysis and Recognition (DAR) is to recognize the text and graphical components of a document and to extract information. This book is a collection of research papers and state-of-the-art reviews by leading researchers all over the world. It includes pointers to challenges and opportunities for future research directions. The main goal of the book is to identify good practices for the use of learning strategies in DAR.
Book Synopsis Biometric Recognition by : Zhenan Sun
Download or read book Biometric Recognition written by Zhenan Sun and published by Springer Nature. This book was released on 2019-10-05 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: The LNCS volume 11818 constitutes the proceedings of the 14th Chinese Conference on Biometric Recognition, held in Zhuzhou, China, in October 2019. The 56 papers presented in this book were carefully reviewed and selected from 74 submissions. The papers cover a wide range of topics such as face recognition and analysis; hand-based biometrics; eye-based biometrics; gesture, gait, and action; emerging biometrics; feature extraction and classification theory; and behavioral biometrics.
Book Synopsis Advances in Neural Information Processing Systems 9 by : Michael C. Mozer
Download or read book Advances in Neural Information Processing Systems 9 written by Michael C. Mozer and published by MIT Press. This book was released on 1997 with total page 1128 pages. Available in PDF, EPUB and Kindle. Book excerpt: The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. It draws preeminent academic researchers from around the world and is widely considered to be a showcase conference for new developments in network algorithms and architectures. The broad range of interdisciplinary research areas represented includes neural networks and genetic algorithms, cognitive science, neuroscience and biology, computer science, AI, applied mathematics, physics, and many branches of engineering. Only about 30% of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. All of the papers presented appear in these proceedings.
Book Synopsis Multiple Classifier Systems by : Terry Windeatt
Download or read book Multiple Classifier Systems written by Terry Windeatt and published by Springer. This book was released on 2003-08-03 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: The refereed proceedings of the 4th International Workshop on Multiple Classifier Systems, MCS 2003, held in Guildford, UK in June 2003. The 40 revised full papers presented with one invited paper were carefully reviewed and selected for presentation. The papers are organized in topical sections on boosting, combination rules, multi-class methods, fusion schemes and architectures, neural network ensembles, ensemble strategies, and applications
Book Synopsis Multiple Classifier Systems by : Josef Kittler
Download or read book Multiple Classifier Systems written by Josef Kittler and published by Springer. This book was released on 2003-06-26 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the First International Workshop on Multiple Classifier Systems, MCS 2000, held in Cagliari, Italy in June 2000.The 33 revised full papers presented together with five invited papers were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on theoretical issues, multiple classifier fusion, bagging and boosting, design of multiple classifier systems, applications of multiple classifier systems, document analysis, and miscellaneous applications.
Book Synopsis Optimization in the Agri-Food Supply Chain by : Mayssa Koubaa
Download or read book Optimization in the Agri-Food Supply Chain written by Mayssa Koubaa and published by John Wiley & Sons. This book was released on 2024-08-29 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the optimization of supply chains in the agri-food and animal industries, and focuses on the integration of technology and sustainability practices. It explores the use of emerging technologies like IoT, Blockchain and AI in supply chain management, and also addresses the need for resilient supply chains and strategies for risk management. Optimization in the Agri-Food Supply Chain provides an overview of various studies conducted in the field, including topics such as the impact of climate change, sustainable initiatives, inventory management activities and the dynamics of specific supply chain systems. It also discusses the use of underutilized crops, optimization techniques, forecasting methods, circular production and the role of open innovation in the food supply chain. Overall, the book aims to contribute to the knowledge on supply chain optimization and also provide insights and recommendations for enhancing efficiency and sustainability in the agri-food and animal industries.
Book Synopsis Multiple Classifier Systems by : Jón Atli Benediktsson
Download or read book Multiple Classifier Systems written by Jón Atli Benediktsson and published by Springer. This book was released on 2009-06-10 with total page 551 pages. Available in PDF, EPUB and Kindle. Book excerpt: These proceedings are a record of the Multiple Classi?er Systems Workshop, MCS 2009, held at the University of Iceland, Reykjavik, Iceland in June 2009. Being the eighth in a well-established series of meetings providing an inter- tional forum for the discussion of issues in multiple classi?er system design, the workshop achieved its objective of bringing together researchers from diverse communities (neural networks,pattern recognition,machine learning and stat- tics) concerned with this research topic. From more than 70 submissions, the Program Committee selected 54 papers to create an interesting scienti?c program. The special focus of MCS 2009 was on the application of multiple classi?er systems in remote sensing. This part- ular application uses multiple classi?ers for raw data fusion, feature level fusion and decision level fusion. In addition to the excellent regular submission in the technical program, outstanding contributions were made by invited speakers Melba Crawford from Purdue University and Zhi-Hua Zhou of Nanjing Univ- sity. Papers of these talks are included in these workshop proceedings. With the workshop’sapplicationfocusbeingonremotesensing,Prof.Crawford’sexpertise in the use of multiple classi?cation systems in this context made the discussions on this topic at MCS 2009 particularly fruitful.
Book Synopsis Advances in Neural Information Processing Systems 13 by : Todd K. Leen
Download or read book Advances in Neural Information Processing Systems 13 written by Todd K. Leen and published by MIT Press. This book was released on 2001 with total page 1136 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proceedings of the 2000 Neural Information Processing Systems (NIPS) Conference.The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. The conference is interdisciplinary, with contributions in algorithms, learning theory, cognitive science, neuroscience, vision, speech and signal processing, reinforcement learning and control, implementations, and diverse applications. Only about 30 percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. These proceedings contain all of the papers that were presented at the 2000 conference.
