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Smart Infrastructure Inspection Using Aerial Imaging
Civil infrastructure like roadways, bridges, tunnels, pipelines, transmission towers, residential and commercial buildings require continuous monitoring to ensure structural integrity.
Ignitarium-Renesas Pretrained AI libraries Release-2
If you found our previous blog 'Ignitarium Releases Pre-trained AI Applications Library for Renesas RZ/V2L' interesting, we are back with the second release of pretrained AI libraries targeted for Renesas
Redefining Rail Inspection with AI-Based Computer Vision
Railroads are the connective tissue of our world’s infrastructure. But despite their critical role in global transportation and supply chains, most railroad track maintenance begins with a human inspector.
Getting started with formal verification
As design complexity is increasing, the goal of 100% functional coverage becomes harder to achieve even after using constrained random stimulus and directed scenarios, therefore there is a need to
3D LiDAR SLAM – Loop Closure Explained
Robots are all equipped with simultaneous localization and mapping (SLAM) algorithms that help them build a map of its surroundings. For SLAM to produce reliable results, loop closure detection and
3D LiDAR SLAM – Localization Explained
Localization is the process of determining a mobile robot's location in relation to its surroundings. Let's imagine that the area has been mapped out and that the robot has sensors
3D LiDAR SLAM – Graph SLAM Explained
Graph-based SLAM (also known as Graph SLAM) uses a graph to represent the environment and the robot’s pose estimates. It is widely used in many robotics applications like autonomous vehicles,
3D LiDAR SLAM – Scan Matching Explained
Simultaneous Localization and Mapping (SLAM) is a popular technique in robotics that involves building a map of an unknown environment while simultaneously localizing the robot within that environment.
Perceiving the World in-’Depth’ with 3D LiDAR
Simultaneous Localization and Mapping (SLAM) is a technology used in robotics and autonomous systems to create maps of unknown environments while simultaneously tracking the location of the robot within that
Horizontal scaling of Video processing applications
Video is a common data input in the field of Computer Vision & Image processing. For example, in applications such as infrastructure maintenance and defect detection, video is captured from
A guide to a Design Engineer’s approach to Failure Mode & Effects Analysis
In the automotive industry, safety plays an immensely crucial role. All crucial systems of the automobile need to pass stringent functional safety requirements.
AI Model optimisation using OpenVINO
In this article we explore the advantages of making use of the native APIs and runtime engine of OpenVINO to maximize the performance and efficiency of DNN model inference.
Is solid-state LiDAR the key to autonomous driving?
The technology for autonomous vehicles has been around for a while, and major automakers and tech companies worldwide have invested billions of dollars in making it a reality.
Solar Panel defect detection using AI techniques
Solar energy is a source of clean energy, naturally harnessing the power of the sun. When solar panels are deployed to generate electricity, greenhouse gases are not emitted into the
Ignitarium Releases Pre-trained AI Applications Library for Renesas RZ/V2L
Ignitarium is excited to release sample vision AI applications targeted for Renesas RZV2L SMARC Dev Kit.
Adaptive filters for signal processing: a comparative study
In some applications, the system or environment where processing is happening is unknown or time-dependant. In such applications, adaptive filters are required because they possess self-adjusting capabilities.
AI based Battery Management System (BMS) – Inference pipeline on Azure Cloud
Batteries are at the heart of many modern electrical systems - Electric Vehicles (EV), Energy Harvesting Systems are some examples of such applications. In EVs, it is imperative that the
Data Annotation for Video AI projects
Data annotation is the process of adding tags or labels to raw data such as images, videos, text, and audio. These tags form a representation of what class of objects