can i use a pretained model and make an application where i will allow students to register their face and once they are done, they can login to the app and start verifying their face. I want the app to work in way whereby i need not have to take time to collect facial data of every students in the class. I want the data collection to be done while registration of the student to the app.
Hello Sir, thank you for this video, it very helpful. Instead I have a question. Should we need a huge data to a similarity of two different signals? For example I’m having two signals and I want to ensure they are both similar or not. In this case, while using Siamese network, these two signals are enough to input in the network with only one label of (x1, x2, 0) or I need to define more labels to train the network and compute the similarity? How many datas samples are required?
Hello! Interesting Question! A huge dataset would not be required. Around 10-20 samples for each signal would be sufficient. If you use the loss similar to the one described in the code, then we would pair each data sample, and define that as the label. For example, if we have 10 data points each for signal 1 (x1, x2, x3, .., x10) and for signal 2 (y1, y2, y3, .., y10). We would create 3 types of labels (xi, yi, 0), (xi, xj, 1) and (yi, yj, 1). All these labels would now be used for training the network. Hope this makes sense, let me know if you have any further questions.
Sir I am making a facial recognize attendance system using Siamese network the capture image's train successfully but when I want to track image it's not recognize the registered person can you please help me with this I'll pay charge's too but please don't ignore my comment I'm in trouble since 2 day's
