What is recorded here?
Reinterpreted Inception modules through depthwise-separable convolutions and proposed Xception, reporting image-classification gains at similar parameter count to Inception V3.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
First preprint was in 2016; year follows CVPR 2017 publication. The paper does not originate depthwise-separable convolution.
Read the original work
- Chollet: Xception depthwise-separable convolutional architecture — original paper
- Chollet: Xception depthwise-separable convolutional architecture — company research source
This English explanation is an editorial reading view. It does not replace the complete original work or certify its science.
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People and systems
François Chollet
Complete named paper byline. Human research, source-reported system execution and experimental validation are distinct; individual effort shares are not measured.
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English catalogue narrative
Chollet: Xception depthwise-separable convolutional architecture
Reinterpreted Inception modules through depthwise-separable convolutions and proposed Xception, reporting image-classification gains at similar parameter count to Inception V3.
Scientific scope
First preprint was in 2016; year follows CVPR 2017 publication. The paper does not originate depthwise-separable convolution.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
François Chollet
Complete named paper byline. Human research, source-reported system execution and experimental validation are distinct; individual effort shares are not measured.