Rank: 235 based on 463 downloads (last 30 days) and 4 files submitted
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Oswaldo Ludwig

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Company/University
KU Leuven

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Oswaldo Ludwig received the M.Sc. degree in electrical engineering from the Federal University of Bahia, Brazil, in 2004, when he began to teach courses in electrical engineering, such as artificial intelligence, digital control, and digital signal processing. In 2012 he received the PhD degree in electrical engineering from University of Coimbra, where he worked as an assistant professor from 2012 until 2013. Nowadays he is working as a senior researcher at the Department of Computer Science of the KU Leuven. His research interests are in machine learning with application on several fields, such as natural language processing, pedestrian and vehicle detection in the domain of intelligent vehicles, and biomedical data mining.


 

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(last 30 days)
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11 Oct 2013 Support Vector Neural Network (SVNN) A new training method for MLP neural networks based on the same principles of SVM. Author: Oswaldo Ludwig neural networks, machine learning, maximummargin princip..., svm, regularization, pattern recognition 66 10
  • 5.0
5.0 | 1 rating
11 Sep 2012 Feature selector based on genetic algorithms and information theory. The algorithm performs the combinatorial optimization by using Genetic Algorithms. Author: Oswaldo Ludwig feature selection, genetic algorithms, artificial intelligen..., information theory, mutual information, pattern recognition 89 11
  • 3.66667
3.7 | 7 ratings
17 Mar 2011 HOG descriptor for Matlab Image descriptor based on Histogram of Oriented Gradients for gray-level images Author: Oswaldo Ludwig image descriptor, computer vision, artificial intelligen... 280 20
  • 4.30769
4.3 | 13 ratings
04 Nov 2010 MMGDX: a maximum-margin training method for neural networks Maximum-margin training method applicable to MLP in the context of binary classification. Author: Oswaldo Ludwig neural networks, machine intelligence, machine learning, artificial intelligen..., machine vision 28 1
Comments and Ratings by Oswaldo Ludwig View all
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14 Nov 2014 Feature selector based on genetic algorithms and information theory. The algorithm performs the combinatorial optimization by using Genetic Algorithms. Author: Oswaldo Ludwig

Dear Arshi,

Pressão means pressure in my mother tongue, you can set the selective pressure of the GA through this variable, see Equation (10) of:
https://www.researchgate.net/publication/235687343_Improving_the_Generalization_Capacity_of_Cascade_Classifiers

24 Sep 2014 Feature selector based on genetic algorithms and information theory. The algorithm performs the combinatorial optimization by using Genetic Algorithms. Author: Oswaldo Ludwig

Mahyar,

I'm sorry you aren't able to read/interpret the file description: "... The arguments are the desired number of selected features (feat_numb), a matrix X, in which each column is a feature vector example...".

05 May 2014 Support Vector Neural Network (SVNN) A new training method for MLP neural networks based on the same principles of SVM. Author: Oswaldo Ludwig

Dear Alweshah,

The best approach is to tune the values of nneu and the punishing parameter C (which can be set in the line 16 of the code) by cross-validation.

28 Oct 2013 Support Vector Neural Network (SVNN) A new training method for MLP neural networks based on the same principles of SVM. Author: Oswaldo Ludwig

Yes, you can download the paper (see Sections 2, 3, and 4): https://www.researchgate.net/publication/256662118_Eigenvalue_decay_a_new_method_for_neural_network_regularization

24 Jan 2013 HOG descriptor for Matlab Image descriptor based on Histogram of Oriented Gradients for gray-level images Author: Oswaldo Ludwig

Could you explain why it was adopted blockwise normalization? From the best of my knowledge, there is no mathematical foundation behind HOG descriptors, only good sense. This is my version, which was made available to be evaluated by the community. Go ahead, you should make the comparison with other algorithms in your case study (Science is not religion, feel free to doubt and inovate).

Comments and Ratings on Oswaldo Ludwig's Files View all
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14 Nov 2014 Feature selector based on genetic algorithms and information theory. The algorithm performs the combinatorial optimization by using Genetic Algorithms. Author: Oswaldo Ludwig Oswaldo Ludwig

Dear Arshi,

Pressão means pressure in my mother tongue, you can set the selective pressure of the GA through this variable, see Equation (10) of:
https://www.researchgate.net/publication/235687343_Improving_the_Generalization_Capacity_of_Cascade_Classifiers

14 Nov 2014 Feature selector based on genetic algorithms and information theory. The algorithm performs the combinatorial optimization by using Genetic Algorithms. Author: Oswaldo Ludwig arshi

Dear Oswaldo,

Can you please explain the meaning of 'Pressao'......There are no of variables whoz meaning is difficult to be guessed....So can you please provide an algo of the code.

09 Oct 2014 Support Vector Neural Network (SVNN) A new training method for MLP neural networks based on the same principles of SVM. Author: Oswaldo Ludwig mustafa alnasser

can i use it for classification

24 Sep 2014 Feature selector based on genetic algorithms and information theory. The algorithm performs the combinatorial optimization by using Genetic Algorithms. Author: Oswaldo Ludwig Oswaldo Ludwig

Mahyar,

I'm sorry you aren't able to read/interpret the file description: "... The arguments are the desired number of selected features (feat_numb), a matrix X, in which each column is a feature vector example...".

24 Sep 2014 Feature selector based on genetic algorithms and information theory. The algorithm performs the combinatorial optimization by using Genetic Algorithms. Author: Oswaldo Ludwig mahyar

Dear Oswaldo
what is the meaning "15" in Hy=entropia2([y;zeros(1,C)],15)?
Moreover, the Y dimension is not matched with zeros(1,C). because the Dimension of C is equal with number of features whereas the dimension of y is equal the number of input pairs.
So, there is a mismatch dimension to vertcat!
How we can solve this problem?

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