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Optimally combining a cascade of classifiers
2006
Document Recognition and Retrieval XIII
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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]
2006
Lecture Notes in Computer Science
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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]
2016
Lecture Notes in Computer Science
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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
2015
2015 IEEE International Conference on Image Processing (ICIP)
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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]
2005
Lecture Notes in Computer Science
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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
2009
BMC Bioinformatics
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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
2019
Applied Sciences
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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
2013
IOSR Journal of Computer Engineering
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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
2016
Wireless personal communications
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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
2014
Proceedings of the 9th International Conference on Computer Vision Theory and Applications
english
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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
2012
Pattern Recognition
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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
2006
IEEE Transactions on Pattern Analysis and Machine Intelligence
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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
2017
Scientific Reports
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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]
2004
Lecture Notes in Computer Science
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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
2017
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '17
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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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