Book Image

Hands-On Java Deep Learning for Computer Vision

By : Klevis Ramo
Book Image

Hands-On Java Deep Learning for Computer Vision

By: Klevis Ramo

Overview of this book

Although machine learning is an exciting world to explore, you may feel confused by all of its theoretical aspects. As a Java developer, you will be used to telling the computer exactly what to do, instead of being shown how data is generated; this causes many developers to struggle to adapt to machine learning. The goal of this book is to walk you through the process of efficiently training machine learning and deep learning models for Computer Vision using the most up-to-date techniques. The book is designed to familiarize you with neural networks, enabling you to train them efficiently, customize existing state-of-the-art architectures, build real-world Java applications, and get great results in a short space of time. You will build real-world Computer Vision applications, ranging from a simple Java handwritten digit recognition model to real-time Java autonomous car driving systems and face recognition models. By the end of this book, you will have mastered the best practices and modern techniques needed to build advanced Computer Vision Java applications and achieve production-grade accuracy.
Table of Contents (8 chapters)

Problems in face detection

Let's explore these challenges related to face recognition:

  • Face versification versus face recognition
  • One-shot learning

We will also see a high-level solution to these problems.

Face verification versus face recognition

So far, we have seen the image recognition problem, where the model predicted either image at any of the chosen classes or objects, such as is it a car, or perhaps a pedestrian, and so on. In addition to that, we have also seen the object localization and detection, where we put a bounding box to those classes or chosen objects. But for now, that is not important. Anyway, in both the cases, we are interested in establishing whether an image had a certain type of object.

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