ML_Workflow.txt

ML Workflow:
1) Models:
	i) Super Resolution (Done)
		-> Upscale the resoultion of images
		-> Compare the upscaled TMC images with OHRC images
		-> Compare with other models
	ii) Crater Detection (Done)
		-> Detecting Elliptical Objects
		-> Superimposing the above on lunar images
		-> Identifying rim length and possible depth
		-> Compare with other models
	iii) Crater Mapping (Done)
		-> Mapping many craters 
	iv) Depth Estimation (Done-Left)
		-> Calculating the depth of the surface.
		-> Finding Craters/Plateau
		-> Use this information for crater detection
	v) Terrain Classification (Left)
		-> Classifying various regions based on the occurrence/size/type of craters/plateau
		-> Classification based on danger level.
	vi) Terrain Mapping (Left)
		-> Creating a path for the lunar bot to travel
		-> Finding checkpoints based on least resistance and least cost possible
		-> Voice Assisstant
	vii) 3D Interpolation (Left)
		-> Converting the 2D path to 3D visual
2) Metrics and Measurement: (Left)
	i) Tracking each change
	ii) Storing each models' metrics
3) ML Integration:
	i) Linear Chain
		-> Resolution-Crater-Depth Model
	ii) Tree Chain
		-> Terrain Classification
		-> Terrain Mapping
	ii) Optional Chain
		-> 3D Interpolation