- Chapter 16, 17,
*Applied Machine Learning*D.A. Forsyth; get the e-book from the library here. - Very nice Stanford course notes from CS231N
- Tensorflow download install
- Tensorflow tutorials
- PyTorch

- Chapter 17, 18,
*Applied Machine Learning*D.A. Forsyth; get the e-book from the library here. - Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe, Christian Szegedy
- Dropout: A Simple Way to Prevent Neural Networks from Overfitting Nitish Srivastava Geoffrey Hinton Alex Krizhevsky Ilya Sutskever Ruslan Salakhutdinov
- keitakurita wrote a nice blog post explaining various normalization methods here
- Swapout: Learning an ensemble of deep architectures Saurabh Singh, Derek Hoiem, David Forsyth
- ImageNet: ImageNet Large Scale Visual Recognition Challenge, by Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei in International Journal of Computer Vision December 2015, Volume 115, Issue 3, pp. 211–252.
- Pascal: The Pascal Visual Object Classes (VOC) Challenge, by Mark Everingham, Luc Van Gool, Christopher K. I. Williams, John Winn, and Andrew Zisserman, International Journal of Computer Vision, June 2010, Volume 88, Issue 2, pp. 303–338.
- VGGNet: Very Deep Convolutional Networks for Large-Scale Image Recognition by Karen Simonyan and Andrew Zisserman, Proc. Int. Conf. Learned Representations, 2015. You can find a version of this here
- Inception: Going Deeper with Convolutions, by Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich, Proc Computer Vision and Pattern Recognition, 2015. You can find a version of this here
- ResNets: Deep Residual Learning for Image Recognition by Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun, Proc Computer Vision and Pattern Recognition, 2015. You can find a version of this here

- Chapter 18,
*Applied Machine Learning*D.A. Forsyth; get the e-book from the library here. - Selective search: Selective Search for Object Recognition by J. R. R. Uijlings, K. E. A. van de Sande, T. Gevers, and A. W. M. Smeulders, International Journal of Computer Vision September 2013, Volume 104, Issue 2, pp. 154–171.
- R-CNN: Rich feature hierarchies for accurate object detection and semantic segmentation, by R. Girshick, J. Donahue, T. Darrell, and J. Malik, IEEE Conf. on Computer Vision and Pattern Recognition, 2014. You can find a version of this here
- Fast R-CNN: Fast R-CNN, by Ross Girshick, IEEE Int. Conf. on Computer Vision (ICCV), 2015, pp. 1440–1448. You can find a version of this here
- Faster R-CNN: Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks, by Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun, Advances in Neural Information Processing Systems 28 (NIPS 2015). You can find a version of this here
- YOLO: You Only Look Once: Unified, Real-Time Object Detection, by Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi, Proc Computer Vision and Pattern Recognition, 2016. You can find a version of this at here. There’s a home page here
- Grabcut: Interactive foreground extraction using iterated graph cuts C Rother, V Kolmogorov, A Blake - ACM transactions on graphics (TOG), 2004 - dl.acm.org
- GREIG, D., PORTEOUS, B., AND SEHEULT, A. 1989. Exact MAP estimation for binary images. J. Roy. Stat. Soc. B. 51, 271–279.

- Multiple View Geometry in Computer Vision Second Edition Richard Hartley and Andrew Zisserman, Cambridge University Press, March 2004.
- Y. Boykov, O. Veksler and R. Zabih (2001), "Fast approximate energy minimisation via graph cuts", IEEE Transactions on Pattern Analysis and Machine Intelligence, 29, 1222–1239.
- Li Hong and G. Chen, "Segment-based stereo matching using graph cuts," Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004., Washington, DC, USA, 2004, pp. I-I, doi: 10.1109/CVPR.2004.1315016.
- R. Szeliski et al., "A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30, no. 6, pp. 1068-1080, June 2008, doi: 10.1109/TPAMI.2007.70844.
- T. Brox, C. Bregler and J. Malik, "Large displacement optical flow", CVPR 2009
- High Accuracy Optical Flow Estimation Based on a Theory for Warping, Thomas Brox, Andr´es Bruhn, Nils Papenberg, and Joachim Weickert, ECCV, 2004

- "Fully Convolutional Networks for Semantic Segmentation" Jonathan Long∗ Evan Shelhamer∗ Trevor Darrell, 2014
- Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials Philipp Krähenbühl, Vladlen Koltun
- Fast high-dimensional filtering using the permutohedral lattice.A. Adams, J. Baek, and M. A. Davis. Computer Graphics Forum, 29(2), 2010. 2, 5

Some resources:

- ROS home page This has install instructions, tutorials, etc
- Detailed slides, with examples, etc.from Roi Yehoshua at Bar-Ilan U.
- Course, with movies from ETH Zurich
- ROS tutorial page (in case you couldn't find it from link above!)

- Notes on simple tracking and Kalman filters
- Extra notes on Kalman filter with 1D derivation
- Tracking Emerges by Colorizing Videos Carl Vondrick, Abhinav Shrivastava, Alireza Fathi, Sergio Guadarrama, Kevin Murphy, ECCV 2018
- Particle filter slides by Pieter Abbeel
- Particle filter slides by Cyrill Stachniss
- Particle filter notes by Drew Bagnell, scribes Greg Seyfarth, Zachary Batts, David Fouhey
- Bag of LIDAR data of high bay HERE

- My notes on least squares, ICP, and IRLS
- Weighted least squares solutions for rotation translation; very nice notes from Olga Sorkine-Hornung and Michael Rabinovitch
- Slides on ICP from Burgard, Stachniss, Bennewitz, Arras at TU Freiburg
- Notes on robustness and iteratively reweighted least squares
- Robust registration of point sets using iteratively reweighted least squares P. Bergstrom and A.Edlund, Computational Optimization and Applications July 2014, Volume 58, Issue 3, pp 543–561

- Basic slam notes
- Slam with an extended Kalman filter from Stachniss, TU Freiburg; does most details, most of which I omitted
- Notes on movement models for mobile robotsby Andrew Davison
- My notes on simple feature based visual slam
- LSD-Slamis a direct visual slam method; note GITHUB page
- Some notes on 3D reconstruction and perspective cameras
- Tutorial on visual slam at CVPR2014
I found the following particularly helpful

- Visual odometry Stephan Weiss
- Stereo Visual odometryChris Beall
- Dense odometryRichard Newcombe

- Supplementary notes for tutorial slides
- Homogeneous coordinates

- PID control: the basics (My notes)
- Controlling the car speed: some sample code from Ehsan Saleh
- Controlling the car speed: a Jupyter notebook from Ehsan Saleh

- Rough notes on the linear-quadratic regulator
- Very nice introduction to Markov decision processes, byCsaba Szepesvari Algorithms for reinforcement learning
- Rough notes on Markov decision processes
- Notes on policy gradient methods
- Very nice set of notes and resources from OpenAI

- Notes on sampling based motion planning, chapter 5 of Lavalle's book "Planning Algorithms"
- Notes on planning in the presence of dynamics , chapter 14 of Lavalle's book "Planning Algorithms"
- Dubins, L.E. (July 1957). "On Curves of Minimal Length with a Constraint on Average Curvature, and with Prescribed Initial and Terminal Positions and Tangents". American Journal of Mathematics. 79 (3): 497–516.
- J. A. Reeds and L. A. Shepp. Optimal paths for a car that goes both forwards and backwards. Pacific Journal of Mathematics, 145(2):367-393, 1990.
- The open mpl library and app
- My planning notes
- My planning notes, dynamics case
- Motion graphs L. Kovar, M. Gleicher, F. Pighin, SIGGRAPH 02
- Interactive motion generation from examplesO. Arikan and D.A. Forsyth, SIGGRAPH 02
- Interactive control of avatars animated with human motion data J Lee, J Chai, PSA Reitsma, JK Hodgins, NS Pollard, SIGGRAPH 02
- Motion synthesis from annotations O Arikan, DA Forsyth, JF O'Brien… - ACM Transactions on …, 2003 - dl.acm.org