Combining MobileNetV1 and Depthwise Separable convolution bottleneck with Expansion for classifying the freshness of fish eyes

Combining MobileNetV1 and Depthwise Separable convolution bottleneck with Expansion for classifying the freshness of fish eyes

Image classification using Convolutional Neural Network (CNN) achieves optimal performance with a particular strategy. MobileNet reduces the parameter number for learning features by switching from the standard convolution paradigm to the depthwise separable convolution (DSC) paradigm. However, ther...

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Bibliographic Details
Main Authors: Eko Prasetyo, Rani Purbaningtyas, Raden Dimas Adityo, Nanik Suciati, Chastine Fatichah
Format: Article
Language:English
Published: Elsevier 2022-12-01
Series:Information Processing in Agriculture
Subjects:
Depthwise separable convolution
Bottleneck
Classification
Freshness
Fish eye
Residual transition
Online Access:http://www.sciencedirect.com/science/article/pii/S2214317322000026

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