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Is SVM a part of deep learning? 

12 answers found

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.

The experimental results demonstrate the effectiveness of the deep SVM back-end system as compared to state-of-the-art techniques.

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.

The results show that the deep learning techniques outperform the SVM algorithm.

Moreover, the experiments show a good generalization ability of SVM which allows transfer and reuse of trained learning machines.

The study confirms the effectiveness of the proposed scheme compared to the existing supervised classification methods including SVM and Deep Learning.

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.

Image Classification using SVM and CNN
13 Mar 2020  6 citations