Recommended library

Remote Sensing:

• Hajnsek, I., Desnos, Y. L., 2021. Polarimetric synthetic aperture radar: principles and application. Springer Nature.
• Schumann, G., 2021. Earth Observation for Flood Applications - Progress and Perspectives. Elsevier.
• Thenkabail Ph.D., Prasad S., 2015. Remote Sensing of Water Resources, Disasters, and Urban Studies. CRC Press.
• Kraus, K., 2011. Photogrammetry: geometry from images and laser scans. Walter de Gruyter. Vancouver.
• Tupin, F., Inglada, J. and Mercier, G., 2014. Image Processing Techniques for Remote Sensing. Remote Sensing Imagery, pp.123-154.
• Tempfli, K., Huurneman, G., Bakker, W., Janssen, L.L., Feringa, W.F., Gieske, A.S.M., Grabmaier, K.A., Hecker, C.A., Horn, J.A., Kerle, N. and van der Meer, F.D., 2009. Principles of remote sensing: an introductory textbook. ITC.
• Caloz, R. and Collet, C., 2001. Précis de télédétection, Volume 3, Traitements numériques d’images de télédétection. Presses de l’Université du Québec. (in French)
• Provencher, L. and Dubois, J.M.M., 2007. Précis de télédétection. Volume 4, Méthodes de photointerprétation et d’interprétation d’image. Presses de l’Université du Québec. (in French)

Computer vision:

• Hartley, R. and Zisserman, A., 2003. Multiple view geometry in computer vision. Cambridge University press.
• Szeliski, R., 2010. Computer vision: algorithms and applications. Springer Science & Business Media.
• Forsyth, D., 2012. Computer Vision, A Modern Approach. Prentice Hall Professional Technical Reference.
• Goshtasby, A.A., 2012. Image registration: Principles, tools and methods. Springer Science & Business Media.
• Goshtasby, A.A., 2005. 2-D and 3-D image registration: for medical, remote sensing, and industrial applications. John Wiley & Sons.

Data assimilation:

• Asch, M., Bocquet, M. and Nodet, M., 2016. Data assimilation: methods, algorithms, and applications. Society for Industrial and Applied Mathematics.

Data fusion:

• Mitchell, H.B., 2007. Multi-sensor data fusion: an introduction. Springer Science & Business Media.
• Bloch, I., 2003. Fusion d’informations en traitement du signal et des images. Hermes Science Publication, 2. (in French)

Facial recognition (both open-source and commercial cloud-based service):

• OpenCV documentation [link]
• Microsoft Face API documentation [link]
• Face recognition webpage [link] and databases [link]

LiDAR principle and applications:

• Shan, J. and Toth, C.K. ed., 2018. Topographic laser ranging and scanning: principles and processing. CRC press.
• Renslow, M.S. ed., 2012. Manual of airborne topographic LiDAR. American Society for Photogrammetry Remote Sensing.
• LiDAR tutorials by Remote Sensing Applications Center, U.S. Forest Service [link]

Optimization:

• Boyd, S.P. and Vandenberghe, L., 2004. Convex optimization. Cambridge university press. [link]
• Bierlaire, M., 2015, Optimization : principles and algorithms. Luasanne : EPFL Press.
• Culioli, J.C., 2012. Introduction à l’optimisation. Ellipses. (in French)

Pattern recognition and Machine intelligence:

• Bishop, C.M., 2007. Pattern Recognition and Machine Learning. Springer Science & Business Media.
• Duda, R.O., Hart, P.E. and Stork, D.G., 2012. Pattern classification. John Wiley & Sons.
• Géron, A., 2019. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems. O’Reilly Media.
• Goodfellow, I., Bengio, Y., Courville, A. and Bengio, Y., 2016. Deep learning (Vol. 1). Cambridge: MIT press. [link]
• Scikit-learn website

Probability and Stochastic Processes:

• Papoulis, A. and Pillai, S.U., 2002. Probability, random variables, and stochastic processes. Tata McGraw-Hill Education.

Probabilistic robotics/SLAM:

• Thrun, S., Burgard, W. and Fox, D., 2005. Probabilistic robotics. MIT press.

Underwater acoustics:

• Lurton, X., 2002. An introduction to underwater acoustics: principles and applications. Springer Science & Business Media.
• Blondel, P., 2010. The handbook of sidescan sonar. Springer Science & Business Media.
• Legris, M., 2011. Systèmes sonars de bathymétrie et d’imagerie. Support de cours ENSIETA, 2, pp.2011-2012. (in French)
• Debese, N., 2013. Bathymétrie-Sondeurs, Traitement des données Modèles numériques de terrain-Cours Exercices Corrigés (p. 408). Ellipses. (in French)