Optimal linear combinations of neural networks
Neural Networks
IEEE Transactions on Pattern Analysis and Machine Intelligence
Soft combination of neural classifiers: a comparative study
Pattern Recognition Letters
Optimal Linear Combination of Neural Networks for Improving Classification Performance
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Combination Fingerprint Classifier
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
A Theoretical Study on Six Classifier Fusion Strategies
IEEE Transactions on Pattern Analysis and Machine Intelligence
SemQuery: Semantic Clustering and Querying on Heterogeneous Features for Visual Data
IEEE Transactions on Knowledge and Data Engineering
Combining Pattern Classifiers: Methods and Algorithms
Combining Pattern Classifiers: Methods and Algorithms
A Theoretical and Experimental Analysis of Linear Combiners for Multiple Classifier Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hierarchical Shape Classification Using Bayesian Aggregation
SMI '06 Proceedings of the IEEE International Conference on Shape Modeling and Applications 2006
Manufacturing processes recognition of machined mechanical parts using SVMs
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 4
Three-dimensional shape searching: state-of-the-art review and future trends
Computer-Aided Design
Shape-based searching for product lifecycle applications
Computer-Aided Design
A 3d model retrieval method using 2d freehand sketches
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part II
An active learning framework for content-based information retrieval
IEEE Transactions on Multimedia
A unified framework for image retrieval using keyword and visual features
IEEE Transactions on Image Processing
CLUE: cluster-based retrieval of images by unsupervised learning
IEEE Transactions on Image Processing
Parallel consensual neural networks
IEEE Transactions on Neural Networks
Sketch-based 3D engineering part class browsing and retrieval
SBM'06 Proceedings of the Third Eurographics conference on Sketch-Based Interfaces and Modeling
Calligraphic Interfaces: Classifier combination for sketch-based 3D part retrieval
Computers and Graphics
A boosting approach to content-based 3D model retrieval
Proceedings of the 5th international conference on Computer graphics and interactive techniques in Australia and Southeast Asia
Feature selection for enhanced spectral shape comparison
EG 3DOR'10 Proceedings of the 3rd Eurographics conference on 3D Object Retrieval
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We present a probability-based unified search framework composed of semi-supervised semantic clustering and then a constraint-based shape matching. Given a query, we propose to use an ensemble of classifiers to estimate the likelihood of the query belonging to each category by exploring the strengths from individual classifiers. Three descriptors driven by Multilevel-Detail shape descriptions have been used to generate the classifier independently. A weighted linear combination rule, called MCE (Minimum Classification Error), is adapted to support high-quality downstream application of the unified search. Experiments are conducted to evaluate the proposed framework using the Engineering Shape Benchmark database. The results have shown that search effectiveness is significantly improved by enforcing the probability-based semantic constraints to shape-based similarity retrieval.