Archive | Deep Learning for Computer Vision

Phillip Island Penguin Parade

A Gentle Introduction to Channels First and Channels Last Image Formats for Deep Learning

Color images have height, width, and color channel dimensions. When represented as three-dimensional arrays, the channel dimension for the image data is last by default, but may be moved to be the first dimension, often for performance-tuning reasons. The use of these two “channel ordering formats” and preparing data to meet a specific preferred channel […]

Continue Reading 4
Example of Displaying a PIL image using the Default Application

How to Load, Convert, and Save Images With the Keras API

The Keras deep learning library provides a sophisticated API for loading, preparing, and augmenting image data. Also included in the API are some undocumented functions that allow you to quickly and easily load, convert, and save image files. These functions can be convenient when getting started on a computer vision deep learning project, allowing you […]

Continue Reading 2
How to Evaluate Pixel Scaling Methods for Image Classification With Convolutional Neural Networks

How to Evaluate Pixel Scaling Methods for Image Classification With Convolutional Neural Networks

Image data must be prepared before it can be used as the basis for modeling in image classification tasks. One aspect of preparing image data is scaling pixel values, such as normalizing the values to the range 0-1, centering, standardization, and more. How do you choose a good, or even best, pixel scaling method for […]

Continue Reading 4
A Gentle Introduction to the Promise of Deep Learning for Computer Vision

A Gentle Introduction to the Promise of Deep Learning for Computer Vision

The promise of deep learning in the field of computer vision is better performance by models that may require more data but less digital signal processing expertise to train and operate. There is a lot of hype and large claims around deep learning methods, but beyond the hype, deep learning methods are achieving state-of-the-art results […]

Continue Reading 4
Convolutional Neural Networks Taught by Andrew Ng

DeepLearning.AI Convolutional Neural Networks Deep Learning Specialization Course (Review)

Andrew Ng is famous for his Stanford machine learning course provided on Coursera. In 2017, he released a five-part course on deep learning also on Coursera titled “Deep Learning Specialization” that included one module on deep learning for computer vision titled “Convolutional Neural Networks.” This course provides an excellent introduction to deep learning methods for […]

Continue Reading 8