Global Certificate in Educational Image Recognition

• Image Recognition Technologies: Overview of image recognition techniques, including machine learning and deep learning algorithms. • Data Preprocessing: Techniques for preparing and cleaning image data for image recognition systems. • Convolutional Neural Networks (CNNs): In-depth study of CNNs, a popular deep learning model for image recognition. • Transfer Learning: Utilization of pre-trained models and transfer learning to improve image recognition performance. • Image Segmentation: Techniques for dividing images into multiple regions to improve recognition accuracy. • Object Detection: Methods for identifying and locating objects within images. • Facial Recognition: Study of facial recognition systems, including their applications and limitations. • Evaluation Metrics: Techniques for evaluating and improving the performance of image recognition systems. • Privacy and Ethics: Discussion of ethical considerations and privacy concerns related to educational image recognition systems.