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Image Classification Examples

Explore convolutional neural networks that recognize objects, digits, logos, and real-world visual states.

Hot Dog or Not Hot Dog image classification Image classification Hot Dog or Not Hot Dog Train a binary CNN to distinguish hot_dog images from the negative class. View walkthrough Java Duke logo recognition Image classification Duke Logo Recognition Recognize whether a prepared input image contains the Java Duke logo. View walkthrough Parking lot occupancy classification Image classification Parking Lot Occupancy Classify a cropped parking-space image as occupied or free with a convolutional network. View walkthrough MNIST handwritten digit recognition Multiclass image classification Handwritten Digit Recognition Train a CNN on balanced 28-by-28 MNIST images and classify digits from 0 to 9. View walkthrough Lego figure image recognition Image classification Lego Figure Recognition Train a binary RGB classifier to detect whether an image contains a Lego figure. View walkthrough TensorFlow VGGNet16 ImageNet import Image classificationAdvanced TensorFlow VGGNet16 Import Import pretrained TensorFlow/ImageNet weights and run VGGNet16 inference without local training. View walkthrough

Convolutional layers learn local visual patterns such as edges, shapes, and textures while preserving spatial structure.

Yes. Each image must pass through the same resize, channel, and value preprocessing expected by the model input.