An intelligent fruit freshness monitoring system using hydrophobic indicator labels based on methylcellulose, k-carrageenan, and sodium tripolyphosphate, combined with deep learning

ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices

Xiangyu Zhang, Xinyu Zhou, Mengxiao Lin et al. · arXiv (Cornell University) · 2017 · 890 citations · Full text

Computing, Computer Science, Computer Vision +15

Inverted Residuals and Linear Bottlenecks: Mobile Networks for Classification, Detection and Segmentation

Andrew Howard, Andrey Zhmoginov, Liang-Chieh Chen et al. · arXiv (Cornell University) · 2018 · 714 citations · Full text

Computing, Computer Science, Computer Vision +9

Development of a novel colorimetric food package label for monitoring lean pork freshness

Huizhi Chen, Min Zhang, Bhesh Bhandari · LWT · 2018 · 220 citations

Agriculture, Food Science, Nutrition +14

Characterization of electrospun nanofibers and solvent-casted films based on Centaurea arvensis anthocyanin-loaded PVA/κ-carrageenan and comparing their performance as colorimetric pH indicator

Samira Forghani, Fariba Zeynali, Hadi Almasi et al. · Food Chemistry · 2022 · 97 citations

Natural Sciences, Materials Engineering, Materials Science +11

Non-destructive monitoring of apple ripeness using an aldehyde sensitive colorimetric sensor

Yong‐Hoon Kim, Yun Jae Yang, Jin Se Kim et al. · Food Chemistry · 2018 · 92 citations · Full text

Agriculture, Food Science, Horticultural Sciences +17