by 
Find us
United States of America
2100 Geng Road, Suite 210
Palo Alto, CA 94303
Poland
Al. Jerozolimskie 44
00-024 Warsaw
Let us know how we can help
Email address
quality@deepsense.ai
Copyright ⓒdeepsense.ai – All Rights Reserved
Food and Beverages
Food and Beverages
Example use cases
Correct label detection
Correct shape/orientation verification
Detection of contamination presence
Topping/sauce cover defects detection
Surface defects (e.g., cracks, holes) in the product
Product spills detection
Anomaly detection
Moisture presence detection
Correct product arrangement detection
Selected case study
Topping/sauce cover defects detection | Detection of contamination
ChallengeClient asked us to tackle 2 of if their problems on the food production line – sauce smears on the inner packaging of the product as well as detection of correct positioning of the topping of the product.
ApproachOur solution is based on the state-of-the-art detection neural networks. The system has been trained so it is not vulnerable to varying lighting conditions and can recognize the context of the scene, e.g. trigger the alarm when the topping is missing in the central part of the product and not on the edges (subject to the client requirements).
ResultsThe model, was able to identify 99% of faulty products with topping defects and raised 99% correct alarms for sauce smears. The model significantly reduced the need for manual quality control, hence lowered cost.
Automotive
Industrial Goods
Packaging
Other
Food and Beverages
Food and Beverages
Example use cases
Correct label detection
Correct shape/orientation verification
Detection of contamination presence
Topping/sauce cover defects detection
Surface defects (e.g., cracks, holes) in the product
Product spills detection
Anomaly detection
Moisture presence detection
Correct product arrangement detection
Selected case study
Topping/sauce cover defects detection | Detection of contamination
ChallengeClient asked us to tackle 2 of if their problems on the food production line – sauce smears on the inner packaging of the product as well as detection of correct positioning of the topping of the product.
ApproachOur solution is based on the state-of-the-art detection neural networks. The system has been trained so it is not vulnerable to varying lighting conditions and can recognize the context of the scene, e.g. trigger the alarm when the topping is missing in the central part of the product and not on the edges (subject to the client requirements ).
ResultsThe model, was able to identify 99% of faulty products with topping defects and raised 99% correct alarms for sauce smears. The model significantly reduced the need for manual quality control, hence lowered cost.
Automotive
Industrial Goods
Packaging
Other
Get in touch
If you wish to learn more about out offer, products or possibilities to cooperate, just leave your email address. Our team will reach out with all the information you need.