The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
On combining classifiers using sum and product rules
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Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“A number of works have shown that among fusion strategies, the weighted arithmetic mean of per-model outputs is the least sensitive to errors of individual classifiers [50].”
From ModDrop: Adaptive Multi-Modal Gesture Recognition (2016) · cites this paper as [50]
Citations
Cites
Neural networks for pattern recognition
Bishop, C. (1994) · Choice Reviews Online · doi:10.5860/choice.31-5500 · Cited by 18,537
UCI Repository of machine learning databases
Blake, C. L. (1998) · Medical Entomology and Zoology · Cited by 10,582
Kittler, J., Hatef, M., Duin, R. P. W., & Matas, J. (1998) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.667881 · Cited by 5,394
Hansen, L. K., & Salamon, P. (1990) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.58871 · Cited by 4,260
Popular Ensemble Methods: An Empirical Study
Opitz, D., & Maclin, R. (1999) · Journal of Artificial Intelligence Research · doi:10.1613/jair.614 · Cited by 2,953
Neural networks for pattern recognition
Marshall, J. A. (1995) · Neural Networks · doi:10.1016/0893-6080(95)90002-0 · Cited by 1,888
Neural Network Toolbox™ User's Guide
Beale, M. H., Hagan, M., & Demuth, H. B. (2015) · Cited by 1,643
Neural Network Classifiers Estimate Bayesian a posteriori Probabilities
Richard, M. D., & Lippmann, R. P. (1991) · Neural Computation · doi:10.1162/neco.1991.3.4.461 · Cited by 1,004
Optimal Linear Combinations of Neural Networks
Hashem, S. (1997) · Neural Networks · doi:10.1016/s0893-6080(96)00098-6 · Cited by 499
Combining the results of several neural network classifiers
Rogova, G. L. (1994) · Neural Networks · doi:10.1016/0893-6080(94)90099-x · Cited by 404
Cited by
Sorted by citations
Items 101–117 of 117
A new approach in solving illumination and facial expression problems for face recognition
Wong, Y. W., Kah, P. S., & Li, M. A. (2009) · Universiti Utara Malaysia Institutional Repository (Universiti Utara Malaysia) · Cited by 1
A Probabilistic Model for the Cooperative Modular Neural Network
Alexandre, L. A., Campilho, A., & Kamel, M. S. (2003) · Lecture notes in computer science · doi:10.1007/978-3-540-44871-6_2 · Cited by 1
Self-citationMultilevel Data Classification and Function Approximation Using Hierarchical Neural Networks
Selver, M. A., & Guzelis, C. (2010) · Studies in computational intelligence · doi:10.1007/978-3-642-16225-1_8 · Cited by 1
Kuncheva, L. I. (2014) · Wiley eBooks · doi:10.1002/9781118914564.refs · Cited by 1
Lip Analysis for Person recognition
Saeed, U. (2010)
Fuzzily modular single-layer RBF neural networks for solving large-scale classification problems
Gao, D., & Zhen, T. (2005) · IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) · doi:10.1109/fuzzy.2005.1452545
A hierarchical algorithm for multi-feature based fingerprint identification
Chen, F., & Zhou, J. (2010) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2010.5654281
A Kind of Fuzzily Combinative Classifiers for Solving Large-Scale Learning Problems
Gao, D., & Zhu, S. (2005) · IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) · doi:10.1109/fuzzy.2005.1452431
BilVideo-7: VIDEO PARSING, INDEXING AND RETRIEVAL
Baştan, M. (2010) · Bilkent University Institutional Repository (Bilkent University)
A Classifier Ensemble Model and Its Applications
Gao, D., Zhu, S., Wei, C., & Li, Y. (2005)
Probabilistic models for mining imbalanced relational data
Ghanem, A. S. (2009)
Implementation of a Multisensory Strategy for Emotion Recognition
Rivera-Flor, H., Freire, T., Caldeira, E. M. D. O., & Valadão, C. (2019) · Anais do 14º Simpósio Brasileiro de Automação Inteligente · doi:10.17648/sbai-2019-111422
A classifier ensemble model and its applications
Zhu, A. D., Chen, S., & ongli, E. I. (2006) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2005.1556019
(2013) · Wiley eBooks · doi:10.1002/9781118618387.ch5
The Science of Emotion: Decoding and Analysis of Human Emotional Landscape
Marruthachalam, R., Amudha, P., & Sivakumari, S. (2024) · The Springer series in applied machine learning · doi:10.1007/978-3-031-63821-3_1
Deep learning for human motion analysis
Neverova, N. (2016) · theses.fr (ABES) · doi:10.70675/a8cda552zdc96z48c1z979bzac140403e58f · Cited by 13
Metadata
- Authors
- Alexandre, L. A., Campilho, A. C., & Kamel, M.
- Affiliations
- Universidade do Porto (PT)
- University of Waterloo (CA)
- Venue
- Pattern Recognition Letters
- Publisher
- Elsevier BV
- Published
- 2001-10
- Volume
- 22
- Issue
- 12
- Pages
- 1283-1289
- ISSN
- 0167-8655 (ISSN-L)
- OpenAlex
- W2029458478
- Cited by
- 117
- References
- 14
- Citations by year
- 2024: 1 · 2023: 4 · 2022: 4 · 2021: 5 · 2020: 3 · 2019: 2 · 2018: 2 · 2017: 3 · 2016: 4 · 2015: 8 · 2014: 5 · 2013: 6 · 2012: 10
- FWCI
- 2.98
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Pattern Recognition Letters (publishedVersion)
- Funders
- Fundação para a Ciência e a Tecnologia
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning and Data Classification
- Physical Sciences › Computer Science › Artificial Intelligence › Imbalanced Data Classification Techniques
- Physical Sciences › Computer Science › Information Systems › Data Mining and Machine Learning Applications
- Keywords
- classifier combination, ensemble learning, sum rules, product rule, arithmetic mean, geometric mean, binary classification
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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