🕰️ History of CNNs

  1. Block World (1963)

    One of the earliest PhD theses on computer vision described the visual world using simple geometric shapes — a foundational idea in representing scenes computationally.

  2. Summer Vision Project (1966)

    The first ambitious project aimed at simulating computer vision, setting the stage for decades of research in how machines interpret visual data.

  3. Image Segmentation

    A key step in computer vision: extracting groups of pixels that belong together (like objects) using graph algorithms. Segmentation makes it possible to understand the structure of an image.

  4. Feature Extraction

    Instead of trying to recognize an entire pattern at once, it’s far easier (and more effective) to extract important features that represent the object.

  5. Pascal VOC Dataset

    The Pascal Visual Object Classes (VOC) dataset — with its 20 object classes — was one of the first benchmark datasets that highlighted the challenges of object detection and gave us a standard to measure progress.

  6. ImageNet Revolution

    ImageNet, once the largest labeled image dataset, pushed object detection research forward dramatically by providing the huge amounts of data needed to train deep models.

  7. AlexNet Breakthrough (2012)

    The release of the AlexNet CNN architecture was a game-changer. It showed how deep learning could vastly outperform traditional methods on object recognition — and it was just the beginning of modern computer vision.

📚 CNN Course Overview — “Image Classification”

  1. Ahead of Their Time

    Many of the algorithms we use today were already conceptualized in the 1990s — but we lacked the computational power and large-scale datasets like ImageNet to make them practical.

  2. Seeing Like a Human

    The big idea: teaching computers to see the world as humans do — recognizing patterns, shapes, and meaning in pixels.

  3. Beyond Labels

    It’s not just about labeling an image as “dog” or “cat.” The goal is to classify attributes, actions, contexts — everything that brings a static image to life with meaning.

✨ Key Takeaway:

From simple geometric block worlds to today’s deep CNNs, the journey of computer vision is all about mimicking how we see, understand, and interact with the visual world — one pixel at a time.