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 General Idea of the Thesis:
 
 1. Realistic scene with objects of YCB Video data set (self recorded or from data set). 
-2. Retrieve point cloud from scene.
+2. Retrieve 2D data from scene.
 3. Segment point cloud into separate areas for objects.
-4. a) Feed neural network with 3D data for object. Classify object and calculate classification loss (cross entropy loss).
-   b) Feed autoencoder with 3D data for object. Calculate encoding loss.
-5. In testing phase the encoding loss tells us if an object is unknown.
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+4. a) Feed SSD with 2D data for object. Classify object and calculate classification loss (cross entropy loss).
+   b) Feed autoencoder with 2D data for object. Calculate encoding/decoding loss.
+5. In testing phase the encoding/decoding loss tells us if an object is unknown.
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