Identification of vegetables. Apple quality control & checked vegetables list.
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名前 | FotoCheck Hortalizas |
---|---|
バージョン | 0.1.15 |
アップデート | 2024年08月22日 |
サイズ | 12 MB |
カテゴリー | ツール |
インストール | 50+ |
開発元 | Turion Development |
Android OS | Android 7.0+ |
Google Play ID | com.FotoCheckHor |
FotoCheck Hortalizas · 説明
Obtain a prediction of what type of vegetable appears in the image.
Using neural networks, a model has been created that allows a prediction to be made from among eight categories of vegetables:
Kiwis, Lemons, Golden Apples, Oranges, Pears, Bananas, Tomatoes, Carrots.
In addition, a checklist of vegetable quality ratings can be saved. In particular, you can select which vegetables have been tested and what their quality grade was with a rating system from 0 to 3 stars.
New: For apples the application suggests a quality grade and tells if they are damaged or overdone.
The next updates of the application will consist of a transformation of the App to make possible the evaluation with a photograph of the visual quality grade of the vegetables (if they are buckled, with dirt, in bad condition, etc.).
Application initially developed as part of the Final Degree Project "Automatic Pattern Recognition in Mobile Devices", Polytechnic University School of Teruel, University of Zaragoza.
WORKS OFFLINE: Available Anywhere
Using neural networks, a model has been created that allows a prediction to be made from among eight categories of vegetables:
Kiwis, Lemons, Golden Apples, Oranges, Pears, Bananas, Tomatoes, Carrots.
In addition, a checklist of vegetable quality ratings can be saved. In particular, you can select which vegetables have been tested and what their quality grade was with a rating system from 0 to 3 stars.
New: For apples the application suggests a quality grade and tells if they are damaged or overdone.
The next updates of the application will consist of a transformation of the App to make possible the evaluation with a photograph of the visual quality grade of the vegetables (if they are buckled, with dirt, in bad condition, etc.).
Application initially developed as part of the Final Degree Project "Automatic Pattern Recognition in Mobile Devices", Polytechnic University School of Teruel, University of Zaragoza.
WORKS OFFLINE: Available Anywhere