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Toward Category-Level Object Recognition
This volume is a post-event proceedings volume and contains selected papers based on presentations given, and vivid discussions held, during two workshops held in Taormina in 2003 and 2004. The 30 thoroughly revised papers presented are organized in the following topical sections: recognition of specific objects, recognition of object categories, recognition of object categories with geometric relations, and joint recognition and segmentation.
Deep Structure, Singularities, and Computer Vision
This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Deep Structure, Singularities, and Computer Vision, DSSCV 2005, held in Maastricht, The Netherlands in June 2005. The 14 revised full papers and 8 revised poster papers presented were carefully reviewed and selected for inclusion in the book. They represent the current state-of-the-art in understanding the relation between structural, topological information represented by singularities and metric information of signals, shapes, images, and colors.
Metric Learning
Similarity between objects plays an important role in both human cognitive processes and artificial systems for recognition and categorization. How to appropriately measure such similarities for a given task is crucial to the performance of many machine learning, pattern recognition and data mining methods. This book is devoted to metric learning, a set of techniques to automatically learn similarity and distance functions from data that has attracted a lot of interest in machine learning and related fields in the past ten years. In this book, we provide a thorough review of the metric learning literature that covers algorithms, theory and applications for both numerical and structured data....
Adaptive Multimedia Retrieval: User, Context, and Feedback
This book constitutes the thoroughly refereed post-proceedings of the Third International Workshop on Adaptive Multimedia Retrieval, held in September 2005. The 18 revised full papers presented were carefully selected during two rounds of reviewing and improvement. Also included are three invited papers by leading researchers in the area to illustrate the core topics of the workshop: User, Context and Feedback. The papers are organized in topical sections on ranking, systems, spatio-temporal relations, using feedback, using context, and meta data.
Stochastic Analysis, Filtering, and Stochastic Optimization
This volume is a collection of research works to honor the late Professor Mark H.A. Davis, whose pioneering work in the areas of Stochastic Processes, Filtering, and Stochastic Optimization spans more than five decades. Invited authors include his dissertation advisor, past collaborators, colleagues, mentees, and graduate students of Professor Davis, as well as scholars who have worked in the above areas. Their contributions may expand upon topics in piecewise deterministic processes, pathwise stochastic calculus, martingale methods in stochastic optimization, filtering, mean-field games, time-inconsistency, as well as impulse, singular, risk-sensitive and robust stochastic control.
Computer Vision, Graphics and Image Processing
This book constitutes the refereed proceedings of the Indian Conference on Computer Vision, Graphics and Image Processing, ICVGIP 2006, held in Madurai, India, December 2006. Coverage in this volume includes image restoration and super-resolution, image filtering, visualization, tracking and surveillance, face-, gesture-, and object-recognition, compression, content based image retrieval, stereo/camera calibration, and biometrics.
Machine Learning and Knowledge Discovery in Databases
The three volume proceedings LNAI 10534 – 10536 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2017, held in Skopje, Macedonia, in September 2017. The total of 101 regular papers presented in part I and part II was carefully reviewed and selected from 364 submissions; there are 47 papers in the applied data science, nectar and demo track. The contributions were organized in topical sections named as follows: Part I: anomaly detection; computer vision; ensembles and meta learning; feature selection and extraction; kernel methods; learning and optimization, matrix and tensor factorization; networks and graphs; neural networks and deep learning. Part II: pattern and sequence mining; privacy and security; probabilistic models and methods; recommendation; regression; reinforcement learning; subgroup discovery; time series and streams; transfer and multi-task learning; unsupervised and semisupervised learning. Part III: applied data science track; nectar track; and demo track.
Computer Vision - ECCV 2004
The four-volume set comprising LNCS volumes 3021/3022/3023/3024 constitutes the refereed proceedings of the 8th European Conference on Computer Vision, ECCV 2004, held in Prague, Czech Republic, in May 2004. The 190 revised papers presented were carefully reviewed and selected from a total of 555 papers submitted. The four books span the entire range of current issues in computer vision. The papers are organized in topical sections on tracking; feature-based object detection and recognition; geometry; texture; learning and recognition; information-based image processing; scale space, flow, and restoration; 2D shape detection and recognition; and 3D shape representation and reconstruction.
Pattern Recognition
It is both an honor and a pleasure to hold the 27th Annual Meeting of the German Association for Pattern Recognition, DAGM 2005, at the Vienna U- versity of Technology, Austria, organized by the Pattern Recognition and Image Processing (PRIP) Group. We received 122 contributions of which we were able to accept 29 as oral presentations and 31 as posters. Each paper received three reviews, upon which decisions were made based on correctness, presentation, technical depth, scienti?c signi?cance and originality. The selection as oral or poster presentation does not signify a quality grading but re?ects attractiveness to the audience which is also re?ected in the order of appearance of papers in ...
Computer Vision for Biomedical Image Applications
With the rapid increase in the variety and quantity of biomedical images in recent years, we see a steadily growing number of computer vision technologies applied to biomedical applications. The time is ripe for us to take a closer look at the accomplishments and experiences gained in this research subdomain, and to strategically plan the directions of our future research. The scientific goal of our workshop, “Computer Vision for Biomedical Image Applications: Current Techniques and Future Trends” (CVBIA), is to examine the diverse applications of computer vision to biomedical image applications, considering both current methods and promising new trends. An additional goal is to provide ...
