Bibliografia

Barnard, Stephen T., and Martin A. Fischler. 1982. “Computational Stereo.” ACM Computing Surveys 14 (4): 553–72. https://doi.org/10.1145/356893.356896.

Barrow, H. G., and J. M. Tenenbaum. 1981. “Computational Vision.” Proceedings of the IEEE 69 (5): 572–95. https://doi.org/10.1109/PROC.1981.12026.

Barthelme, Simon. 2023. “Imager: Image Processing Library Based on ’CImg’.” https://CRAN.R-project.org/package=imager.

Blake, Andrew, and Michael Isard. 2012. Active Contours: The Application of Techniques from Graphics, Vision, Control Theory and Statistics to Visual Tracking of Shapes in Motion. Springer Science & Business Media.

Blake, Andrew, Andrew Zisserman, and Greg Knowles. 1985. “Surface Descriptions from Stereo and Shading.” Image and Vision Computing, Papers from the 1985 Alvey Computer Vision and Image Interpretation Meeting, 3 (4): 183–91. https://doi.org/10.1016/0262-8856(85)90006-X.

Burger, Wilhelm, and Mark J. Burge. 2016. Digital Image Processing: An Algorithmic Introduction Using Java. Texts in Computer Science. London: Springer. https://doi.org/10.1007/978-1-4471-6684-9.

Canny, John. 1986. “A Computational Approach to Edge Detection.” IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-8 (6): 679–98. https://doi.org/10.1109/TPAMI.1986.4767851.

Chollet, Francois, and J. J. Allaire. 2018. Deep Learning with R. Manning Publications.

Ciresan, Dan C, Ueli Meier, Jonathan Masci, Luca M Gambardella, and Jurgen Schmidhuber. n.d. “Flexible, High Performance Convolutional Neural Networks for Image Classification.”

“Cooperative Computation of Stereo Disparity | Science.” n.d. https://www.science.org/doi/10.1126/science.968482.

Davis, Larry S. 1975. “A Survey of Edge Detection Techniques.” Computer Graphics and Image Processing 4 (3): 248–70. https://doi.org/10.1016/0146-664X(75)90012-X.

“Deep Learning with Python, Second Edition.” n.d. Manning Publications. https://www.manning.com/books/deep-learning-with-python-second-edition.

Dev, Parvati. 1975. “Perception of Depth Surfaces in Random-Dot Stereograms : A Neural Model.” International Journal of Man-Machine Studies 7 (4): 511–28. https://doi.org/10.1016/S0020-7373(75)80030-7.

Felzenszwalb, Pedro F., and Daniel P. Huttenlocher. 2005. “Pictorial Structures for Object Recognition.” International Journal of Computer Vision 61 (1): 55–79. https://doi.org/10.1023/B:VISI.0000042934.15159.49.

Fergus, R., P. Perona, and A. Zisserman. 2007. “Weakly Supervised Scale-Invariant Learning of Models for Visual Recognition.” International Journal of Computer Vision 71 (3): 273–303. https://doi.org/10.1007/s11263-006-8707-x.

Fischler, M., and O. Firschein. 1987. “Readings in Computer Vision: Issues, Problems, Principles, and Paradigms.” In.

Garnier, Simon, and John Muschelli. 2022. “Rvision - a Computer Vision Library for r.” https://swarm-lab.github.io/Rvision/.

Goodfellow, Ian, Yoshua Bengio, and Aaron Courville. 2016. Deep Learning. Illustrated edition. Cambridge, Massachusetts: The MIT Press.

Hanson, Allen. 1978. Computer Vision Systems. Elsevier.

He, Kaiming, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2015. “Deep Residual Learning for Image Recognition.” arXiv. https://doi.org/10.48550/arXiv.1512.03385.

Horn, Berthold K P. n.d. “Obtaining Shape from Shading Information.”

Ioffe, Sergey, and Christian Szegedy. 2015. “Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift.” arXiv. https://doi.org/10.48550/arXiv.1502.03167.

Kass, Michael, Andrew Witkin, and Demetri Terzopoulos. 1988. “Snakes: Active Contour Models.” International Journal of Computer Vision 1 (4): 321–31. https://doi.org/10.1007/BF00133570.

Ketkar, Nikhil, and Eder Santana. 2017. Deep Learning with Python. Vol. 1. Springer.

Kirsch, Russell A. 1971. “Computer Determination of the Constituent Structure of Biological Images.” Computers and Biomedical Research 4 (3): 315–28. https://doi.org/10.1016/0010-4809(71)90034-6.

Krizhevsky, Alex, Ilya Sutskever, and Geoffrey E. Hinton. 2017. “ImageNet Classification with Deep Convolutional Neural Networks.” Communications of the ACM 60 (6): 84–90. https://doi.org/10.1145/3065386.

LeCun, Yann, Yoshua Bengio, and Geoffrey Hinton. 2015. “Deep Learning.” Nature 521 (7553): 436–44. https://doi.org/10.1038/nature14539.

Malladi, R., J. A. Sethian, and B. C. Vemuri. 1995. “Shape Modeling with Front Propagation: A Level Set Approach.” IEEE Transactions on Pattern Analysis and Machine Intelligence 17 (2): 158–75. https://doi.org/10.1109/34.368173.

Marr, D., and E. Hildreth. 1980. “Theory of Edge Detection.” Proceedings of the Royal Society of London. Series B, Biological Sciences 207 (1167): 187–217. https://doi.org/10.1098/rspb.1980.0020.

“Mind as Machine: A History of Cognitive Science.” 2007. Choice Reviews Online 44 (11). https://doi.org/10.5860/choice.44-6202.

Mundy, Joseph L., and Andrew Zisserman, eds. 1992. Geometric Invariance in Computer Vision. Cambridge, MA, USA: MIT Press.

Nalwa, Vishvjit S., and Thomas O. Binford. 1986. “On Detecting Edges.” IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-8 (6): 699–714. https://doi.org/10.1109/TPAMI.1986.4767852.

Niedballa, Juergen, and Jan Axtner. 2022. “Imageseg: Deep Learning Models for Image Segmentation.” https://CRAN.R-project.org/package=imageseg.

Ochi, Shota. 2019. “imagerExtra: Extra Image Processing Library Based on ’Imager’.” https://CRAN.R-project.org/package=imagerExtra.

Olivoto, Tiago. 2021. “Pliman: Tools for Plant Image Analysis.” https://CRAN.R-project.org/package=pliman.

Ooms, Jeroen. 2023. “Magick: Advanced Graphics and Image-Processing in r.” https://CRAN.R-project.org/package=magick.

“Optical and Electro-Optical Information Processing.” n.d. MIT Press.

“Picture Processing and Psychopictorics - 1st Edition.” n.d. https://www.elsevier.com/books/picture-processing-and-psychopictorics/lipkin/978-0-12-451550-5.

Ponce, Jean, Martial Hebert, Cordelia Schmid, and Andrew Zisserman. 2007. Toward Category-Level Object Recognition. Springer.

Roberts, Lawrence G. 1980. Machine Perception of Three-dimensional Solids. Garland Pub.

Ronneberger, Olaf, Philipp Fischer, and Thomas Brox. 2015. “U-Net: Convolutional Networks for Biomedical Image Segmentation.” arXiv. https://doi.org/10.48550/arXiv.1505.04597.

Selvaraju, Ramprasaath R., Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra. 2020. “Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization.” International Journal of Computer Vision 128 (2): 336–59. https://doi.org/10.1007/s11263-019-01228-7.

Simonyan, Karen, and Andrew Zisserman. 2014. “Very Deep Convolutional Networks for Large-Scale Image Recognition.” https://doi.org/10.48550/ARXIV.1409.1556.

Szeliski, Richard. 2022. Computer Vision: Algorithms and Applications. Texts in Computer Science. Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-34372-9.

Winston, Patrick Henry. 1976. “The Psychology of Computer Vision.” Pattern Recognition 8 (3): 193. https://doi.org/10.1016/0031-3203(76)90020-0.

Witkin, Andrew P. 1981. “Recovering Surface Shape and Orientation from Texture.” Artificial Intelligence 17 (1): 17–45. https://doi.org/10.1016/0004-3702(81)90019-9.

Woodham, Robert J. 1981. “Analysing Images of Curved Surfaces.” Artificial Intelligence 17 (1): 117–40. https://doi.org/10.1016/0004-3702(81)90022-9.

Zhang, T. Y., and C. Y. Suen. 1984. “A Fast Parallel Algorithm for Thinning Digital Patterns.” Communications of the ACM 27 (3): 236–39. https://doi.org/10.1145/357994.358023.

Zhou, Zongwei, Md Mahfuzur Rahman Siddiquee, Nima Tajbakhsh, and Jianming Liang. 2018. “UNet++: A Nested U-Net Architecture for Medical Image Segmentation.” arXiv. https://doi.org/10.48550/arXiv.1807.10165.