Note: All images in this directory, unless specified otherwise, are licensed under CC BY-NC 4.0.
Figure number | Description |
---|---|
10-1 | The Bach music harmonizer doodle from Google |
10-2 | Screenshot of DeepTraffic training a car with reinforcement learning using ConvNetJS |
10-3 | Benchmarking data for ResNet-50 on different JavaScript machine learning libraries on CPU |
10-4 | Benchmarking data for ResNet-50 on different JavaScript machine learning libraries on GPU |
10-5 | A high-level overview of the TensorFlow.js and ml5.js ecosystem |
10-6 | Class prediction output in the browser |
10-7 | Training live in the browser with Teachable Machine |
10-8 | Predictions by our model on a webcam feed within a browser |
10-9 | GPU utilization shown in the Google Chrome profiler view |
10-10 | The top predicted classes with the probability of each class |
10-11 | Keypoints drawn using PoseNet on a picture of former President Obama in a snowball fight |
10-12 | Example of input and output pairs on pix2pix |
10-13 | A flowchart for a GAN |
10-14 | Sketch-to-image example |
10-15 | We can create colored blueprints (left) and pix2pix will convert them to realistic-looking human faces (right) |
10-16 | Training pairs for pix2pix: a B&W image and its original color image |
10-17 | Pix2Pix: Edges to Pikachu by Yining Shi, built on ml5.js |
10-18 | Inference time for MobileNetV1 in Chrome on different devices |
10-19 | Inference time in different browsers on iPhone X |
10-20 | Inference time in different browsers on an i7 @ 2.6 GHz macOS 10.14 machine |
10-21 | Control an orchestra by waving your arms on the Semi-Conductor demonstrator |
10-22 | LeNet model visualized inside TensorSpace |
10-23 | Metacar environment for training with reinforcement learning |
10-24 | Screenshot of GAN Lab |