Van Vung Pham – författare

Explore Detectron2 using cutting-edge models and learn all about implementing future computer vision applications in custom domainsPurchase of the print or Kindle book includes a free PDF eBookKey FeaturesLearn how to tackle common computer vision tasks in modern businesses with Detectron2Leverage Detectron2 performance tuning techniques to control the model’s finest detailsDeploy Detectron2 models into production and develop Detectron2 models for mobile devicesBook DescriptionComputer vision is a crucial component of many modern businesses, including automobiles, robotics, and manufacturing, and its market is growing rapidly. This book helps you explore Detectron2, Facebook's next-gen library providing cutting-edge detection and segmentation algorithms. It’s used in research and practical projects at Facebook to support computer vision tasks, and its models can be exported to TorchScript or ONNX for deployment.The book provides you with step-by-step guidance on using existing models in Detectron2 for computer vision tasks (object detection, instance segmentation, key-point detection, semantic detection, and panoptic segmentation). You’ll get to grips with the theories and visualizations of Detectron2’s architecture and learn how each module in Detectron2 works. As you advance, you’ll build your practical skills by working on two real-life projects (preparing data, training models, fine-tuning models, and deployments) for object detection and instance segmentation tasks using Detectron2. Finally, you’ll deploy Detectron2 models into production and develop Detectron2 applications for mobile devices.By the end of this deep learning book, you’ll have gained sound theoretical knowledge and useful hands-on skills to help you solve advanced computer vision tasks using Detectron2.What you will learnBuild computer vision applications using existing models in Detectron2Grasp the concepts underlying Detectron2's architecture and componentsDevelop real-life projects for object detection and object segmentation using Detectron2Improve model accuracy using Detectron2's performance-tuning techniquesDeploy Detectron2 models into server environments with easeDevelop and deploy Detectron2 models into browser and mobile environmentsWho this book is forIf you are a deep learning application developer, researcher, or software developer with some prior knowledge about deep learning, this book is for you to get started and develop deep learning models for computer vision applications. Even if you are an expert in computer vision and curious about the features of Detectron2, or you would like to learn some cutting-edge deep learning design patterns, you will find this book helpful. Some HTML, Android, and C++ programming skills are advantageous if you want to deploy computer vision applications using these platforms.

This book constitutes the refereed proceedings of the first International Conference on Cybersecurity, IoT, Data Science and Digital Forensics, CIDDF 2025, held in The Woodlands, Texas, USA, during October 2–4, 2025.The 13 full papers and one short paper included in this book were carefully reviewed and selected from 29 submissions. These papers focused on topics such as digital forensics and security analytics; the use of data science, machine learning, and visualization for security and forensic analysis; multimodal AI and intelligent systems; and IoT and system security.