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Optimizing Inception for Computer Vision by Maria Palancares is a document available to read on EtoBox.

What is Optimizing Inception for Computer Vision about?

The document proposes general design principles for convolutional neural networks based on extensive experimentation. These principles include avoiding representational bottlenecks, using higher dimensional representations, balancing network width and depth, and factorizing convolutions with large filter sizes. The paper also discusses scaling up Inception-style networks in an efficient manner while maintaining high model quality.

Author

Maria Palancares

Language

EN