Support Vector Machines – An Introduction
By Vojislav Kecman. 2005
405 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition
View Paper: https://www.semanticscholar.org/paper/b079568f9804cd9f7eb67b78b3c07922e1511164
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- D. Lord
- Suhail Yousaf
- Yunlong Zhang
- Iftikhar Ahmad
- Muhammad Ovais Ahmad
- Muhammad Nadeem Yousaf
- Yuanchang Xie
- Xiugang Li
In Computer Vision and Pattern Recognition
- D. Lord
- Suhail Yousaf
- Yunlong Zhang
- Iftikhar Ahmad
- Muhammad Ovais Ahmad
- Muhammad Nadeem Yousaf
- Yuanchang Xie
- Xiugang Li
Citations in the corpus
- Fake News Detection Using Machine Learning Ensemble Methods (2020, methodology): “A mathematical representation of the cost function for the SVM model is defined as given in [30] and shown in such that function above uses a linear kernel.”
- Predicting motor vehicle crashes using Support Vector Machine models. (2008, background): “It has been found that SVMs show better or comparable results than the outcomes estimated by neural networks and other statistical models (Kecman, 2005).”