Deep Learning CNN Convolutional Neural Networks with Python - Sliding Window Implementation

The video tutorial explains the process of object detection using a feature extractor and classifier. It discusses the challenges of handling unknown test data, especially when dealing with large images. The sliding window technique is introduced as a solution to process large images by extracting small patches. The video also covers feature extraction and classification, highlighting the importance of descriptors. Finally, it addresses challenges like object orientation and position, hinting at future solutions.

Describe the process of how a classifier determines if an object is present in a patch.

How does the classifier provide feedback on the presence of an object in a patch?

What challenges arise when the object to be detected is not centered in the image?