Fresh Scanner

About project

An AI platform that offers surveyors automated quality control and fruit and vegetable categorization.
Working with Fresh Scanner
Working with Fresh Scanner

Facts

A team of 6 members, consisting of 3 software developers.
80.000$ budget.
Revolutionary technology applied.

Customer

under NDA

Our customer is a former top manager of one of the largest Russian retailers and leads a world-class surveyor and logistics professionals.

Goal

  • Accuracy of 99%
  • Defects Detection
  • Product Quality Detection
  • Quality Category Detection
  • Databases conducted in the accordance with the UNECE and OECD standards

Challenge

  • Our software streamlines the dataset and feature management, training pipeline for Artificial Neural Networks (ANNs), and deployment process.

  • Our neural network algorithms efficiently evaluate the freshness of fruits and vegetables.
  • Our software solution covers all essential surveyor processes, including product analysis, shipment analysis, and statistical analysis.
  • Our examination result databases are extensive and meet the standards set by the United Nations Economic Commission for Europe (UNECE) and the Organization for Economic Cooperation and Development (OECD).

Results

1

A scanner for obtaining high-quality photographs has been developed.

2

A unit of trade professionals has been formed to assess the quality of fruits and vegetables.

3

Data collection for machine learning is ongoing.

4

Developed software to assess the quality of fruits and vegetables.

5

The automated process of forming reports has been developed.

6

The virtual personal Cabinet of the expert-receiver has been developed.

Presentation

Download presentation of the project (3.66 Mb)

Technologies

Basic technologies
1
  • C#
  • Microsoft.NET
  • Python
Artificial intelligence
2
  • Convolutional neural networks
  • ResNET
  • RetinaNET

Screenshots

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