DDD Blog
Our thoughts and insights on machine learning and artificial intelligence applications
Welcome to Digital Divide Data’s (DDD) blog, fully dedicated to Machine Learning trends and resources, new data technologies, data training experiences, and the latest news in the areas of Deep Learning, Optical Character Recognition, Computer Vision, Natural Learning Processing, and more.
For Artificial Intelligence (AI) professionals, adding the latest machine learning blog or two to your reading list will help you get updates on industry news and trends.
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Enhancing Safety Through Perception: The Role of Sensor Fusion in Autonomous Driving Training
Autonomous vehicles need to interpret their surroundings accurately and make informed decisions in real-time. Sensor fusion, a cutting-edge technology, holds the key to improving perception and safety in autonomous driving.
High-Quality Training Data for Autonomous Vehicles in 2023
How is this training data obtained? Who can help you gather high-quality training data for autonomous vehicles in 2023? In this guide, we'll discuss all of that. So, let’s begin!
Everything You Need To Know About Computer Vision
Computer vision has made it possible to detect and label objects, being able to accomplish tasks that humans can’t.
4 Major Regulatory Hurdles in the Autonomous Driving Space
Regulations for autonomous driving typically focus on two key areas: safety and performance. This article is mostly focused on the regulatory and legislative hurdles regarding safety of automated driving and autonomous vehicles.
Determining The New Gold Standard of Autonomous Driving
Emerging standards are beginning to regulate how manufacturers approach navigation, safety, and AD modeling quality. These standards also influence policy creation, technology use, and the general framework for AD systems. Creating standard systems for these AD models will lead to a more uniform approach toward autonomous driving models.
How Data Labeling and Annotation Are Fueling Autonomous Driving’s Global Movement
Autonomous driving is becoming more prevalent worldwide. With that growing interest comes an emerging need for experts who can develop the tools and processes necessary for driver behavior monitoring, self-parking, motion planning, and traffic mapping.
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