Computer vision is the field of AI that focuses on the development of algorithms and models that enable computers to understand and interpret visual data from the world, such as images and videos. In this course, we will explore the fundamentals of computer vision, including image processing, object recognition, and advanced techniques such as convolutional neural networks (CNN).
Image Processing: Image processing is the process of manipulating and analyzing digital images. It involves techniques such as image enhancement, image restoration, and image analysis. Image processing is used to improve the quality of an image, extract information from it, and prepare it for further analysis.
Object Recognition: Object recognition is the process of identifying and locating objects within an image or video. Object recognition algorithms use features such as color, shape, and texture to identify objects. These algorithms can be used for tasks such as image classification, object detection, and object tracking.
Convolutional Neural Networks (CNN): CNNs are a type of deep learning architecture that is particularly well-suited for image and video analysis. CNNs are designed to automatically and adaptively learn features from input images and are composed of multiple layers of artificial neurons. The layers of a CNN include convolutional layers, pooling layers, and fully connected layers. These layers work together to extract features from an image and classify it into different categories.
Applications of Computer Vision: Computer Vision techniques are widely used in several domains such as:
- Self-driving cars: object detection, lane following, and decision making
- Surveillance systems: object detection and tracking
- Robotics: visual servoing, visual SLAM, and visual odometry
- Healthcare: medical image analysis and diagnosis
- Augmented Reality: object detection and recognition.
In this course, students will learn the fundamentals of computer vision, including image processing, object recognition, and advanced techniques such as CNNs. They will also explore various applications of computer vision in different fields and have the opportunity to work on a hands-on project to apply their knowledge and skills to a real-world problem.