Computer Vision A Modern Approach 2nd Edition Pdf Download __LINK__
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The book does not look at the optimization issues in deep learning models. It does not look at applications of deep learning methods to other areas such as computer vision, natural language processing, time series, etc. All the examples look at data sets based on tabular information such as health care, financial, marketing, etc. I have doubts whether such a set of examples will be sufficient to cover all the modern applications of deep learning models and none of the examples look at the multimodal aspects of deep learning. Therefore I suggest the authors to carefully think about the scope of the book and the purpose of the book and cover the field of computer vision, natural language processing, time series, and even machine translation, etc. The final two chapters (8 and 9) should be included in the book (as an appendix) where the authors can give a formal justification of the regularization approach to deep learning. In addition the authors can try to avoid the reliance on cross validation (which is not a rigorous method of model selection). These are the points that I would like to see covered if the authors proceed with their idea of writing a book on deep learning.
The following list of applications may help the reader to get anidea of applications of computer vision and machine learningapproaches. - Facial recognition- Object recognition- Human action recognition- Audio and visual event detection- Object tracking and vehicle detection- Pedestrian detection- Person re-identification
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