Field
Computer Vision
Getting machines to make sense of images.
Computer vision was the first field deep learning conquered decisively. In 2012 AlexNet won ImageNet by a margin that ended the argument, and the modern era started there.
The field is organised by how much you need to know about an image. Image classification says what's in it. Object detection says where. Segmentation labels every pixel, which is what you need when the exact shape matters and you can afford the annotation. OCR reads the text — solved for clean scans, genuinely hard for everything else.
That last one carries the field's most useful warning: OCR's "solved" reputation causes real project failures, because handwriting, phone photos, and layout-carrying documents are different problems wearing the same name.
Start with Image Classification — everything else builds on it.
4 concepts in this field
Image Classification
Getting an AI to look at an image and say what it is — the foundational task of computer vision.
Object Detection
Finding where objects are in an image and what they are — drawing a labelled box around each one.
Image Segmentation
Labelling every pixel rather than drawing a box — what you need when the exact shape matters.
OCR (Optical Character Recognition)
Turning pictures of text into text — solved for clean documents, still genuinely hard for everything else.