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This repository contains study material that I've gathered over the years during master's degree.

Books


Computer Vision:

harris-corners, sift.

kmeans, gaussian-mixture-model, gmm-overview - siraj raval , intro-to-gmm, expectation-maximization, bayes-theorem.

fundamental-matrix, 8 point algo, epipolar-overview, epipolar-6min.

morphology-dilation, morphology-Erosion, morphology-example, connected-components--row by row, Recursive Connected Components.

camera-calibration

stereo-rectification, stereo-code,

barycentric-coordinates1, barycentric-coordinates2, barycentric-coordinates3, inversewarping

Python Bundle adjustment, PnP, BundleAdjustment, Thin plate Spline.

camera-motion-estimation-using-optical-flow depth-estimation

Lectures:

Basic CV lectures, Photogrammetry-Cyrill Stachniss. SLAM-Cyril Stachniss


Deep Learning

stat453:DL-101 cheatsheet softmax, Torch Basics, roi-pooling-align object-detection, andrej-karpathy-blogs colah-blogs: understanding-lstms batch-norm

Lectures

Soheil Feizi Lectures, cs231n, cmsc828i cs224n-nlp cs229-ml


Convex Optimization

Optimization Algorithms, understanding BFGS


Algebra:

Principal Axes Theorem, Parametric equations of line and plane, svd-stevebrunton

Lectures

By Dr. Gilbert Strang : linear-algebra-101, Matrix-methods


Control Systems:

By Steve Brunton control-bootcamp


Planning:

motion-planning-short rrt

Lectures:

Computational Geometry and Planning, cs326-motion-planning, cognitive-robotics, robotic-manipulation.


Robot Modeling:

Angela sodemann's dh-kinematics-dynamics,

misc:

all DL lecture list dl-drizzle

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