# Vision Models

> Classification, detection, segmentation, embeddings, vision transformers, data augmentation, and visual evaluation.

Canonical: https://learn.significanthobbies.com/curriculum/concepts/vision-models

Classification, detection, segmentation, embeddings, vision transformers, data augmentation, and visual evaluation.

- Difficulty: core
- Tracks: Multimodal & Spatial Computing

## Mental model

Vision systems convert pixels into task-specific spatial representations. Architecture, labels, augmentations, resolution, and evaluation must match deployment conditions.



## Primary sources

- [Stanford CS231n](https://cs231n.stanford.edu/) (doc)

## Practice

### Design exercise: Vision Models

Classification, detection, segmentation, embeddings, vision transformers, data augmentation, and visual evaluation. Implement designOutline() returning non-empty values for: taskDefinition, representation, visualEval. Each value must name a concrete mechanism or decision.

**Expected evidence:** A design outline with taskDefinition, representation, visualEval plus an explicit failure mode or trade-off.

## Review prompts

- Why do CNNs still often beat vision transformers on small datasets?

## Build evidence

- **Synthesize: AI Models & Training** — Move from transformer foundations through pre-training, fine-tuning, post-training, compression, and evaluation. Produce one working system, benchmark, or evidence-backed design that integrates the path.
- **Synthesize: Multimodal & Spatial Computing** — Connect vision, audio, generation, on-device intelligence, robotics, spatial interfaces, and HCI. Produce one working system, benchmark, or evidence-backed design that integrates the path.

## Prerequisites

- None assigned.

## Related concepts

- [Multimodal Models](https://learn.significanthobbies.com/curriculum/concepts/multimodal-models)
- [Voice & Audio Systems](https://learn.significanthobbies.com/curriculum/concepts/voice-audio-systems)

## Learning paths

- [12-Week AI Models & Training](https://learn.significanthobbies.com/curriculum/roadmaps/ai-models-training-12w)
- [12-Week Multimodal & Spatial Computing](https://learn.significanthobbies.com/curriculum/roadmaps/multimodal-spatial-12w)