Is SVM a part of deep learning?
Answers from top 12 papers
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| Papers (12) | Insight |
|---|---|
12 Jul 2015 273 Citations | Thus, executing deep learning requires heavy computation, so deep learning is usually utilized with parallel computation with many cores or many machines. |
| Recently, it is found that SVM in some cases is equivalent to MLC in probabilistically modeling the learning process. | |
01 Oct 2017 5 Citations | The experimental results demonstrate the effectiveness of the deep SVM back-end system as compared to state-of-the-art techniques. |
12 Jul 2015 6 Citations | As a result, deep features are reliably extracted without additional feature extraction efforts, using multiple layers of the SVM with GMM. |
| Support Vector Machine(SVM)is one of novel learning machine methods, its advantages are simple structure, strong compatibility, global optimization, least raining time and better generalization. | |
| It was found that deep-learning methodologies perform better than SVM methodology in normal or abnormal classification. | |
01 Jan 2019 30 Citations | The results show that the deep learning techniques outperform the SVM algorithm. |
53 Citations | Moreover, the experiments show a good generalization ability of SVM which allows transfer and reuse of trained learning machines. |
11 Jan 2019 | The study confirms the effectiveness of the proposed scheme compared to the existing supervised classification methods including SVM and Deep Learning. |
178 Citations | It is found that the deep learning-based method provides a more accurate classification result than the traditional ones. |
| These results highlight the relevance of an appropriate choice of the image representation before SVM learning. | |
| This stands as a testimony to the increased potential of deep learning techniques over the more traditional machine learning techniques. |
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