Normalizing images is a crucial step in data preprocessing for object detection tasks. This article explores the importance of normalization in Python using OpenCV and scikit-image libraries.
Official Python documentation provides a comprehensive guide to object detection, including data preprocessing techniques such as normalization, using popular libraries like TensorFlow and Keras.
Research paper discussing various preprocessing techniques for object detection, including normalization, feature scaling, and data augmentation, with a focus on deep learning approaches.
OpenCV provides a range of tools and techniques for image normalization, a critical step in object detection pipelines. This tutorial demonstrates how to normalize images using OpenCV in Python.
Video tutorial covering the basics of data preprocessing for object detection, including normalization, data augmentation, and feature scaling, using Python and popular deep learning libraries.
Stanford University's computer vision course provides a comprehensive overview of data preprocessing techniques, including normalization, for object detection and other computer vision tasks.
Tutorial on building an object detection model using Python, Keras, and TensorFlow, with a focus on data preprocessing techniques such as normalization and data augmentation.
The National Institute of Standards and Technology provides guidelines and best practices for data preprocessing in object detection, including normalization, feature scaling, and data quality assessment.