# Visión por Computador

## Docs

- [Bibliography & Resources](https://mintlify.wiki/domingomery/vision/bibliography.md): Core textbooks, supplementary videos, and reference materials for the course.
- [Course Overview](https://mintlify.wiki/domingomery/vision/course-overview.md): Schedule, chapter structure, grading, and exam resources for Visión por Computador (IEE3714 / IIC3724).
- [Facial Analysis](https://mintlify.wiki/domingomery/vision/deep-learning/facial-analysis.md): Face detection, recognition, and social attribute analysis
- [Generative Models: GANs & Diffusion](https://mintlify.wiki/domingomery/vision/deep-learning/generative-models.md): Generative adversarial networks and diffusion-based image synthesis
- [Image Classification with CNNs](https://mintlify.wiki/domingomery/vision/deep-learning/image-classification-cnn.md): Convolutional neural networks for image classification
- [Introduction to Deep Learning](https://mintlify.wiki/domingomery/vision/deep-learning/introduction.md): Foundations of deep learning for computer vision
- [Object Detection with YOLO](https://mintlify.wiki/domingomery/vision/deep-learning/object-detection-yolo.md): Real-time object detection, tracking, and anomaly detection
- [Image Segmentation with UNet](https://mintlify.wiki/domingomery/vision/deep-learning/segmentation-unet.md): Semantic segmentation using the UNet architecture
- [Vision Transformers](https://mintlify.wiki/domingomery/vision/deep-learning/transformers.md): Attention mechanisms, ViT, and multimodal vision-language models
- [Explainability and Interpretability](https://mintlify.wiki/domingomery/vision/ethics/explainability.md): Methods for explaining AI model decisions, including saliency maps and the MinPlus algorithm
- [Fairness and Bias in AI](https://mintlify.wiki/domingomery/vision/ethics/fairness-bias.md): Understanding and mitigating algorithmic bias in computer vision systems
- [Ethics in AI and Computer Vision](https://mintlify.wiki/domingomery/vision/ethics/introduction.md): Motivations, challenges, and responsibilities in AI-powered computer vision systems
- [Camera Calibration](https://mintlify.wiki/domingomery/vision/geometry/camera-calibration.md): Estimating intrinsic and extrinsic camera parameters using DLT, SVD, and RANSAC.
- [Homogeneous Coordinates](https://mintlify.wiki/domingomery/vision/geometry/homogeneous-coordinates.md): Points, lines, and planes in projective space — the foundational language of computer vision geometry.
- [Homographies](https://mintlify.wiki/domingomery/vision/geometry/homographies.md): Planar homographies and their applications in geometric rectification and image mosaics.
- [Multiple View Geometry](https://mintlify.wiki/domingomery/vision/geometry/multiple-view-geometry.md): Epipolar geometry, fundamental matrix, essential matrix, and 3D reconstruction from two or three views.
- [2D and 3D Transformations](https://mintlify.wiki/domingomery/vision/geometry/transformations.md): Euclidean, similarity, affine, and projective transformations in 2D and 3D, represented as homogeneous matrices.
- [Introduction to Computer Vision](https://mintlify.wiki/domingomery/vision/introduction.md): An overview of the field of computer vision — what it is, where it comes from, and how this course approaches it.
- [Exam Preparation](https://mintlify.wiki/domingomery/vision/resources/exam-preparation.md): Past exam questions, solutions, and study resources for the Computer Vision course final exam.
- [Practice Exercises](https://mintlify.wiki/domingomery/vision/resources/exercises.md): Hands-on in-class exercises with Python (Colab) for each course topic, from geometry to deep learning.

## OpenAPI Specs

- [openapi](https://mintlify.wiki/domingomery/vision/api-reference/openapi.json)