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4. Deep Neural Networks Why Deep ? Logistic Regression and Single Layer Neural Networks perform well on some Simple Binary Classification Problems Deep Neural Networks (or Deep Learning) can solve more complex problems Neuroscientists believe that the human brain also starts off detecting simple things like edges to complex things like faces Layers “learn” simpler functions to more complex functions Face Detection: The first layer of the neural network could be considered as Edge Detector each hidden unit may figure out different edge orintation (horizontal or vertical edges) The second layer could group the edges detected in first layer together different units may detect different parts of faces (eyes, noses,.

Index – Simple NN – Deep NN – CNN, U-Net, YOLO – PointNets ==> 3D object dection – Pose Estimation 1. Neural Network History Neural networks rose to fame (成名) in the late 1980s, fall from favor (失宠) because some “new methods” such as SVMs, Boosting, and Random Forests were more automatic and outperformed poorly-trained neural networks on many problems for the first decade in the new millennium (2000 - 2010)

Relative Pose Estimation Recent Progress and New Methods 相对位姿估计的进展和新方法 深蓝学院公开课，赵季老师 1. Pose Estimation Categorization Pose from 3D - 3D (for point clouds) point cloud registration ICP, NDT, LOAM, .. Pose from 3D - 2D (for image and map) absolute pose estimation P3P, perspective-n-point (PnP), .. Pose from 2D - 2D (for image with overlap) relati

Registration: Find a Transform to align two point clouds A transform consists of Rotation R and Translation t Applications: Odometry(里程计)/SLAM Mapping Loop Closure Calibration Object Pose Estimation Problem Definition Given two

The tutorial report may consists of separate sections that teach different aspects/options within a SAS procedure. You will write about: Explanation in your own word of how a certain options works in the SAS procedure. Example SAS code applied on the any of the three data set Interpretation of the output from the example SAS code. You should be able to explain these clearly in your report. Final Project 1.