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Hi, Thanks for your work. I have used the model nn4.small2.lrn.h5 for extracting the features after re-running Keras-openface-convertion.ipynb.
I got worst accuracy while applied with minimum / euclidean distance classifier for one shot face authentication (one image per class) compared with dlib feature extractor.
Am I doing right ?
Does the model work for one shot learning or not ?
Thanks and regards.
Bhanuchander
The text was updated successfully, but these errors were encountered:
I have analyzed this one shot learning technique with various transfer learning models... I feel like it seems learning with small set of data not worthy even doing one shot learning (It really doing bad with real time test set).... May be with more data (with large learning time and resource) It will be possible to get decent results...
I did small analysis for face_recognition task with a best i ever tested face feature extractor keras-vggface even compared with dlib. Reference analysis.
Hi, Thanks for your work. I have used the model
nn4.small2.lrn.h5
for extracting the features after re-runningKeras-openface-convertion.ipynb
.I got worst accuracy while applied with minimum / euclidean distance classifier for one shot face authentication (one image per class) compared with dlib feature extractor.
Am I doing right ?
Does the model work for one shot learning or not ?
Thanks and regards.
Bhanuchander
The text was updated successfully, but these errors were encountered: