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World Congress 2025 • Aug 20, 2025 • Session details

Is it (F)ake?! Image Classification with TensorFlow.js

Carly Richmond

Is it real, or is it a hyper-realistic cake? Learn how developers can use TensorFlow.js and transfer learning to build accurate computer vision classifiers without an ML background.

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#1 about 4 min

Exploring machine learning and image classification in JavaScript

An exploration of building and utilizing machine learning models for visual classification using an unconventional dataset.

#2 about 3 min

Building an image dataset for a binary classifier

Extracting images utilizing testing frameworks and external APIs allows for the creation of a balanced training dataset.

#3 about 3 min

Using the predefined MobileNet model for image classification

Decoding images into multi-dimensional tensors enables the evaluation of pre-trained image models for baseline accuracy.

#4 about 2 min

Identifying elements with the COCO-SSD object detection model

Leveraging single-shot multi-box detection draws targeted bounding boxes to isolate and classify specific objects within an image.

#5 about 6 min

Building a custom convolutional neural network in Node.js

Constructing a sequential model with convolution and pooling layers creates custom decision neurons for domain-specific visual predictions.

#6 about 5 min

Applying transfer learning to improve classification dataset accuracy

Combining existing feature vectors with a custom classification head leverages established pre-trained patterns to overcome small dataset limitations.

#7 about 5 min

Comparing human accuracy against machine learning model predictions

An interactive web application demonstrates the difficulty of complex visual parsing tasks for both human logic and algorithmic models.

#8 about 2 min

Lessons learned on understanding how machine learning models work

Investigating layer mechanics and pre-trained model reuse provides software engineers with a practical foundation for working with visual classifiers.

Matching moments

2:36 min

Experimenting with JavaScript machine learning for cake detection

Carly Richmnd · Coffee With Developers

5:05 min

Evaluating MobileNet and COCO-SSD pre-trained computer vision models

Carly Richmonds · LIVE

4:43 min

Introduction to image classification and the cake detection challenge

Carly Richmonds · LIVE

4:13 min

Implementing machine learning with Core ML and Vision

MIlan Todorović MIlan Todorović · WWC 2025

2:57 min

Sourcing and preparing custom images for a binary dataset

Carly Richmonds · LIVE

6:13 min

Building a custom Convolutional Neural Network pipeline from scratch

Carly Richmonds · LIVE

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