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Optimally combining a cascade of classifiers

Kumar Chellapilla, Michael Shilman, Patrice Simard, Kazem Taghva, Xiaofan Lin
2006 Document Recognition and Retrieval XIII  
A branch-and-bound version of depth-first-search with efficient pruning is proposed for finding the optimal thresholds for the cascade.  ...  We propose a novel search based approach to automatically combine multiple classifiers in a cascade to obtain the desired tradeoff between classification speed and classification accuracy.  ...  A preliminary investigation into optimizing a cascade of classifiers for speed can be found in [8] .  ... 
doi:10.1117/12.643669 dblp:conf/drr/ChellapillaSS06 fatcat:jjswwl7py5az7pa5jboamhkqpq

Combining Multiple Classifiers for Faster Optical Character Recognition [chapter]

Kumar Chellapilla, Michael Shilman, Patrice Simard
2006 Lecture Notes in Computer Science  
We propose a cascade architecture for combining classifiers and cast the process of building such a cascade as a search and optimization problem.  ...  In this paper we present a novel approach to combining multiple classifiers to solve the inverse problem of significantly improving classification speeds at the cost of slightly reduced classification  ...  Conclusion A cascade architecture for combining classifiers was presented along with four algorithms for optimization.  ... 
doi:10.1007/11669487_32 fatcat:nadswcopuzfvzmklpudmujwfda

Ordering of Visual Descriptors in a Classifier Cascade Towards Improved Video Concept Detection [chapter]

Foteini Markatopoulou, Vasileios Mezaris, Ioannis Patras
2016 Lecture Notes in Computer Science  
The proposed cascade is more accurate and computationally more efficient, in terms of classifier evaluations, than state-of-the-art classifier combination approaches.  ...  This work proposes an algorithm that dynamically selects, orders and combines many base classifiers, trained independently with different feature-based keyframe representations, in a cascade architecture  ...  A second category of classifier combination approaches performs ensemble pruning to select a subset of the classifiers prior to their fusion.  ... 
doi:10.1007/978-3-319-27671-7_73 fatcat:tlf3jnrbnfbi3ldefzvohniequ

Cascade of classifiers based on binary, non-binary and deep convolutional network descriptors for video concept detection

Foteini Markatopoulou, Vasileios Mezaris, Ioannis Patras
2015 2015 IEEE International Conference on Image Processing (ICIP)  
In addition, this work presents a detailed study on combining descriptors based on Deep Convolutional Neural Networks with other popular local descriptors, both within a cascade and when using different  ...  In this paper we propose a cascade architecture that can be used to train and combine different visual descriptors (local binary, local non-binary and Deep Convolutional Neural Network-based) for video  ...  Fig. 1 . 1 (a) Block diagram of the proposed cascade architecture. (b) Stage combining many base classifiers trained on different features.  ... 
doi:10.1109/icip.2015.7351108 dblp:conf/icip/MarkatopoulouMP15 fatcat:45pw6hetrbgjdhswcdt66dshse

Cascade AdaBoost Classifiers with Stage Optimization for Face Detection [chapter]

Zongying Ou, Xusheng Tang, Tieming Su, Pengfei Zhao
2005 Lecture Notes in Computer Science  
AdaBoost algorithm selects a set of weak classifiers and combines them into a final strong classifier.  ...  However, conventional AdaBoost is a sequential forward search procedure using the greedy selection strategy, the weights of weak classifiers may not be optimized.  ...  A cascade of face classifiers is a decision tree where at each stage a classifier is trained and formed to detect almost all frontal faces while rejecting a certain fraction of non-face patterns.  ... 
doi:10.1007/11608288_17 fatcat:2n7knlizufbxxmjwgtnisbroii

PCI-SS: MISO dynamic nonlinear protein secondary structure prediction

James R Green, Michael J Korenberg, Mohammed O Aboul-Magd
2009 BMC Bioinformatics  
The three-state prediction problem is broken down into a combination of three binary sub-problems and protein structure classifiers are built using 2 layers of PCI classifiers.  ...  When PCI is used to combine a sequence-to-structure PCI-based classifier with the current leading ANN-based method, PSIPRED, the overall error rate (Q3) is maintained while the rate of occurrence of a  ...  Acknowledgements This study was supported by grants from the Natural Sciences and Engineering Research Council of Canada.  ... 
doi:10.1186/1471-2105-10-222 pmid:19615046 pmcid:PMC2720391 fatcat:cmvueasihfcijegm6t574ixudi

Evaluation of Classical Machine Learning Techniques towards Urban Sound Recognitionon Embedded Systems

Bruno da Silva, Axel W. Happi, An Braeken, Abdellah Touhafi
2019 Applied Sciences  
In addition, a cascade approach is also proposed to combine ML techniques by exploiting embedded characteristics such as pipeline or multi-thread execution present in current embedded devices.  ...  Automatic urban sound classification is a desirable capability for urban monitoring systems, allowing real-time monitoring of urban environments and recognition of events.  ...  The main benefit of the cascade approach is the combination of classifiers.  ... 
doi:10.3390/app9183885 fatcat:ygddzopl5zdarpqpizdjgvvvbm

A Novel Learning Formulation in a unified Min-Max Framework for Computer Aided Diagnosis

Sree Kanth
2013 IOSR Journal of Computer Engineering  
To address all these problems, we propose a novel learning formulation to combine cascade classification and multiple instance learning (MIL) in a unified min-max framework, leading to a joint optimization  ...  Experimental results show that our approach significantly reduces the computational cost while yielding comparable detection accuracy to the current state-of-the-art MIL or cascaded classifiers.  ...  In this paper, we propose a novel approach to combine MIL classifiers in a cascade. In particular, we start out with formulating MIL as an optimization problem in a min-max framework in Section 2.  ... 
doi:10.9790/0661-1344452 fatcat:x3ufrrdjpff4pf65uh4vrvggsi

Waterfall Traffic Classification: A Quick Approach to Optimizing Cascade Classifiers

Paweł Foremski, Christian Callegari, Michele Pagano
2016 Wireless personal communications  
In this paper, we describe a modular, cascading traffic classification system-the Waterfall architecture-and we extensively describe a novel technique for its optimization-in terms of CPU time, number  ...  We employ five datasets of real Internet transmissions and seven traffic analysis methods to demonstrate that our proposal yields valid results and outperforms a greedy optimizer.  ...  In a 2006 paper, Chellapilla et al. [21] propose a cascade optimization algorithm that updates the rejection thresholds of the constituent classifiers.  ... 
doi:10.1007/s11277-016-3751-5 fatcat:6ud7locusjglpety2baxf2heyi

Towards Reliable Real-time Person Detection
english

Silviu-Tudor Serban, Srinidhi Mukanahallipatna Simha, Vasanth Bathrinarayanan, Etienne Corvée, François Brémond
2014 Proceedings of the 9th International Conference on Computer Vision Theory and Applications  
We introduce a comprehensive training method based on random sampling that compiles optimal classifiers with minimal bias and overfit rate.  ...  We propose a robust real-time person detection system, which aims to serve as solid foundation for developing solutions at an elevated level of reliability.  ...  Cascading and Random sampling We use random sampling to construct cascades of optimized classifiers. A random sampling classification stage is a seemingly exhaustive process.  ... 
doi:10.5220/0004651302320239 dblp:conf/visapp/SerbanSBCB14 fatcat:yhwpllxvpbd7vlnhzj7doqz6hu

Pedestrian detection in images via cascaded L1-norm minimization learning method

Ran Xu, Jianbin Jiao, Baochang Zhang, Qixiang Ye
2012 Pattern Recognition  
Finally, a cascade of LML classifiers is constructed to promote detection speed.  ...  In the strong classifier learning, an integer programming optimization model is built, equaling the reformulation of LML in the integer space.  ...  This work is supported by the National Basic Research Program of China (973 Program) with nos. 2011CB706900, 2010CB731800 and the National Science Foundation of China with nos. 60872143 and 61039003.  ... 
doi:10.1016/j.patcog.2012.01.004 fatcat:ocjttfmzobeq3i3gn2yikf4uji

An Experimental Study on Pedestrian Classification

S. Munder, D.M. Gavrila
2006 IEEE Transactions on Pattern Analysis and Machine Intelligence  
A boosted cascade of Haar wavelets can, however, reach quite competitive results, at a fraction of computational cost.  ...  Our experiments show that the novel combination of SVMs with LRF features performs best.  ...  For each stage of the cascade, AdaBoost [14] iteratively constructs a weighted linear combination of simple classifiers, each made by thresholding one feature value.  ... 
doi:10.1109/tpami.2006.217 pmid:17063690 fatcat:gece4fdvlzaendwqqpiwyinv74

Cascaded Multi-view Canonical Correlation (CaMCCo) for Early Diagnosis of Alzheimer's Disease via Fusion of Clinical, Imaging and Omic Features

Asha Singanamalli, Haibo Wang, Anant Madabhushi
2017 Scientific Reports  
by selectively combining a subset of modalities at each level of the cascade.  ...  In this work, we present a combined framework, cascaded multiview canonical correlation (CaMCCo), for fusion and cascaded classification that incorporates all diagnostic categories and optimizes classification  ...  CaMCCo seeks to fuse a subset of modalities from T1w MRI, FDG PET, ApoE, CSF, plasma proteomics and neurophysiological exam scores in order to optimize classifier performance at each level of the cascade  ... 
doi:10.1038/s41598-017-03925-0 pmid:28811553 pmcid:PMC5558022 fatcat:f4zpwwuwezfojgje6tljzloye4

Automatic Design of Cascaded Classifiers [chapter]

Etienne Grossmann
2004 Lecture Notes in Computer Science  
This classifier is then "sliced" using dynamic programming into a cascade of classifiers in a nearly computation-cost-optimal fashion.  ...  We propose to automatically build a cascade of classifiers, given just a family of weak classifiers a desired performance level and little more.  ...  set of the boosted classifier. b) Nearly optimal in terms of the computational cost of the classifier, amongst all cascades that verify a).  ... 
doi:10.1007/978-3-540-27868-9_108 fatcat:73oahnggwza7pcjeygtv4nw6re

Learning Tree-Structured Detection Cascades for Heterogeneous Networks of Embedded Devices

Hamid Dadkhahi, Benjamin M. Marlin
2017 Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '17  
at each node.To accomplish the objective of joint learning of all detectors, we propose a novel approach to combining classifier outputs during training that better matches the hard cascade setting in  ...  We concentrate on the problem of jointly learning the parameters for all of the classifiers in the cascade given a fixed cascade architecture and a known set of costs required to carry out the computation  ...  Acknowledgments The authors would like to thank Deepak Ganesan, Nazir Saleheen, and Santosh Kumar for helpful discussions of this research.  ... 
doi:10.1145/3097983.3098169 pmid:29333328 pmcid:PMC5765542 dblp:conf/kdd/DadkhahiM17 fatcat:fnjpeeb575hsfa2ektwsozdyt4
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