Relu

With the rapid development of technology in all life fields, and due to the huge daily needs for banking systems process, documents processing and other similar systems. The authentication became more required key for these systems. One of the successful system to verify the any person is the signature verification system. However, a reliable and accurate system is still needed. For this reason, the security challenge is take place via authentic signatures. However, a reliable and accurate system is still needed. For this reason, the security challenge is take place via authentic signatures. Therefore, this paper present a reliable signature verification system using proposed histogram of sparse codes (HSC) feature extraction approach and artificial neural networks (ANN) architecture for classification. The system achieved fast computing 0.09 ms and accurate verification results that is 99.7% using three different signature images datasets CEDAR, UTSig, and ICDAR.

There have been times when we’re outside, having fast food, and we wonder about the food that we’re having. Is it healthy, what is its caloric content, how much protein, fat it contains? So we decided to create an AI/ML model, train it on images of 10 fast foods, in the hope that it correctly identifies whatever fast food is thrown at it, along with the nutrition details of the respective food item.