Enroll Course: https://www.coursera.org/learn/deteccion-objetos
If you’re fascinated by computer vision and eager to understand how machines recognize objects within images, the Coursera course ‘Detección de objetos’ is an excellent choice. This course provides a solid foundation in object detection, covering essential methods and advanced techniques used in the field.
The course begins with fundamental concepts, including image analysis, correlation, and convolution, which are crucial for designing simple object detectors. It then delves into classification methods using window classifiers, illustrating approaches like Local Binary Patterns (LBP) with logistic regression.
One of the core components is the object detection pipeline, where the course explains how to generate candidate regions and use classifiers to confirm object presence. Notable detection systems such as HOG/SVM and Haar/Adaboost are examined in detail, complete with training and evaluation procedures.
The final module explores advanced techniques, including non-holistic models, domain adaptation, convolutional neural networks (CNNs), multi-modal image analysis, and innovative candidate generation methods. These topics prepare students to handle complex detection scenarios and stay abreast of current research trends.
Overall, I highly recommend this course for students, professionals, or enthusiasts eager to learn about the core and cutting-edge methods in object detection. Its structured approach, practical examples, and comprehensive content make it a valuable resource for anyone interested in computer vision.
Whether you are looking to build your skills for academic research or practical applications like surveillance, autonomous vehicles, or image search engines, this course provides the necessary tools and knowledge to succeed.
Enroll Course: https://www.coursera.org/learn/deteccion-objetos