Ulteriori informazioni
This book constitutes the thoroughly refereedpost-conference proceedings of the Third International Conference on PatternRecognition, ICPRAM 2014, held in Angers, France, in March 2014.
The 18 revised full papers were carefully reviewed andselected from 179 submissions and describe up-to-date applications of PatternRecognition techniques to real-world problems, interdisciplinary research,experimental and/or theoretical studies yielding new insights that advancePattern Recognition methods.
Sommario
Multiple Image Segmentation.- Aggregation of Biclustering Solutions for Ensemble Approach.- Fuzzy C-Means Stereo Segmentation.- SCHOG Feature for Pedestrian Detection.- Learning Prior Bias in Classifier.- Intra-class Variance among Multiple Samples of the Same Person's Fingerprint in a Cooperative User Scenario.- Kernel Matrix Completion for Learning Nearly Consensus Support Vector Machines.- An Empirical Comparison of Support Vector Machines versus Nearest Neighbour Methods for Machine Learning Applications.- Improving the Detection of Relations between Objects in an Image using Textual Semantics.- A ToF-based Approach to 3D Reconstruction of Isometric Surfaces.- Segmentation of Tomatoes in Open Field Images with Shape and Temporal Constraints.- Fast and Accurate Pedestrian Detection in a Truck's Blind Spot Camera.- Comparing Different Labeling Strategies in Anomalous Power Consumptions Detection.- An Efficient Shape Feature Extraction, Description and Matching Method using GPU.- Utilization of Multiple Sequence Analyzers for Bibliographic Information Extraction.
Riassunto
This book constitutes the thoroughly refereed
post-conference proceedings of the Third International Conference on Pattern
Recognition, ICPRAM 2014, held in Angers, France, in March 2014.
The 18 revised full papers were carefully reviewed and
selected from 179 submissions and describe up-to-date applications of Pattern
Recognition techniques to real-world problems, interdisciplinary research,
experimental and/or theoretical studies yielding new insights that advance
Pattern Recognition methods.
