What is the process for training a deep learning model to accurately detect and classify objects in images, specifically focusing on the keyword "label image" for object detection?

Training a deep learning model to accurately detect and classify objects in images involves several steps. First, a large dataset of labeled images is needed, where each image is associated with the objects it contains. The deep learning model is then trained using this dataset through a process called "labeling images," where the model learns to recognize and classify objects based on the labels provided in the training data. This process involves feeding the images into the model, adjusting the model's parameters based on the errors it makes, and repeating this process until the model can accurately detect and classify objects in new, unseen images.