Inception (deep learning architecture)
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Comment: Probably a notable topic, but needs sources PrussianOwl (talk) 03:24, 25 March 2019 (UTC)
Inceptionv3[1] is the name of a data set sometimes used in a Convolutional_neural_network for assisting in Image_analysis and Object_detection, and got its start as a module for GoogLeNet. Just as ImageNet can be thought of as a database of classified visual objects, Inception helps classification of objects[2] in the world of Computer_vision. One such use is in Life Sciences, where it aids in the research of Leakumia[3]. As referenced at DeepDream it was "codenamed 'Inception' after the film of the same name".
References
- ^ Shlens, Jon. "Train your own image classifier with Inception in TensorFlow". ai.googleblog.com. Retrieved 4 April 2019.
- ^ Karim and Zaccone (March 2018). Deep Learning with TensorFlow. Packt Publishing. pp. Chapter 4. ISBN 9781788831109.
- ^ Milton-Barker, Adam. "Inception V3 Deep Convolutional Architecture For Classifying Acute Myeloid/Lymphoblastic Leukemia". intel.com. Intel. Retrieved 2 February 2019.
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