AI for Augmented Reality refers to the use of artificial intelligence to enhance and improve augmented reality experiences. AI helps AR systems recognise objects, understand environments, and respond to user actions more intelligently. This combination allows digital content to interact more naturally and accurately with the real world, making AR applications more useful and engaging.
Category: Computer Vision
AI for Lip Syncing
AI for lip syncing uses artificial intelligence to match spoken words or audio with the movement of lips in videos or animations. This technology analyses the sounds and generates corresponding mouth shapes, making characters or people appear as if they are really speaking the audio. It is commonly used in film, animation, video games, and…
AI for Video Analysis
AI for video analysis refers to the use of artificial intelligence technologies to automatically interpret, process, and understand video content. This can include recognising objects, tracking movement, detecting activities, and even summarising or searching through hours of footage. By analysing video data, AI can help save time, improve accuracy, and provide insights that would be…
AI for Image Recognition
AI for image recognition refers to the use of artificial intelligence systems to analyse and understand the content of images. These systems can identify objects, people, scenes, or even specific details within a picture. By learning from large sets of labelled images, AI can quickly and accurately spot patterns that help it make sense of…
AI for Medical Imaging
AI for medical imaging refers to the use of artificial intelligence technologies to help analyse images such as X-rays, CT scans, and MRIs. These systems can quickly identify patterns or signs of diseases that might be difficult for humans to spot. This helps doctors make faster and more accurate diagnoses, which can lead to better…
AI for Autonomous Drones
AI for autonomous drones refers to the use of artificial intelligence to allow drones to operate without direct human control. By processing data from sensors and cameras, AI enables drones to make decisions such as navigating obstacles, choosing flight paths, and responding to changing environments. This technology helps drones perform complex tasks safely and efficiently,…
Squeeze-and-Excitation Modules
Squeeze-and-Excitation Modules are components added to neural networks to help them focus on the most important features in images or data. They work by learning which channels or parts of the data are most useful for a task, and then highlighting those parts while reducing the influence of less useful information. This process helps improve…
Spatio-Temporal Neural Networks
Spatio-Temporal Neural Networks are artificial intelligence models designed to process data that changes over both space and time. They are particularly good at understanding patterns where the position and timing of data points matter, such as videos, traffic flows, or weather patterns. These networks combine techniques for handling spatial data, like images or maps, with…
Quantised Vision-Language Models
Quantised vision-language models are artificial intelligence systems that understand and relate images and text, while using quantisation techniques to reduce the size and complexity of their data. Quantisation involves converting continuous numerical values in the models to a smaller set of discrete values, which helps make the models faster and less resource-intensive. This approach allows…
Visual QA Platform
A Visual QA Platform is a software tool that helps teams test and review the look and behaviour of digital products, such as websites or apps, by providing visual feedback. It allows users to spot design differences, check for errors, and make comments directly on screenshots or live interfaces. These platforms streamline the process of…