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3D point cloud matching vs. 3D point cloud to 2D projection matching
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Classroom Contents
Pose Estimation, Temperature, Noise, and Biological Temperature Sensors via Cryo-EM
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- 1 Intro
- 2 What is a biological temperature sensor?
- 3 A THERMODYNAMIC FRAMEWORK FOR TRP CHANNEL TEMPERATURE SENSING
- 4 3D point cloud matching vs. 3D point cloud to 2D projection matching
- 5 Why quaternions?
- 6 A discontinuity when going from rotation matrix to quaternion space!
- 7 Part II: Analytical solution to the 3D pose estimation problem.
- 8 The Determinant Ratio Matrix (DRAM) Approach
- 9 Summary: Improved framework for quaternion pose estimation.
- 10 An interlude about noise.
- 11 Cryo-EM allows access to a conformational distribution.
- 12 A quick introduction to Manifold Embedding.
- 13 Belief propagation in Manifold Embedding.
- 14 Manifold Embedding: Apo TRPV1 dataset
- 15 An apoferritin for heterogeneity?
