Our advanced AI-driven computer vision solutions elevate products through automated image analysis and sophisticated imaging on devices.
In the data centre and on the edge, we craft and deploy tailored solutions that effortlessly identify persons of interest, ensure compliance with health and safety standards, detect stress and key actions, and uncover valuable insights from video and radar data. We can help your business to unlock
From Vision to Action
Object Detection
Instantly detect and locate specific objects, people, and patterns within images and videos. Effortlessly enable applications like facial recognition, object tracking, and intrusion detection.
Techniques
Our advanced detection capabilities can identify multiple objects within an image or video frame in real-time, thanks to frameworks such as YOLO (You Only Look Once), SSD (Single Shot MultiDetector), and Faster R-CNNs. They combine deep learning with classical computer vision techniques like bounding boxes and anchor boxes to locate object positions with high precision. This makes them ideal for surveillance, quality inspection, and retail environments.
Optical Character Recognition (OCR)
Instantly convert text from documents and complex surfaces into digital data, enabling applications like automated data entry and document digitisation.
Techniques
Our OCR technology uses deep learning to transform typed, handwritten, or printed text into machine-encoded text. Using advanced neural networks like CNNs, RNNs, and LSTMs, our system accurately recognises and converts characters from different document formats and languages. Complex layouts and diverse fonts are handled with minimal preprocessing, while integrated attention mechanisms focus on specific text areas sequentially.
Automatic Annotation
Rapidly annotate and label large datasets with precision and accuracy. Create customised datasets by greatly reducing the manual effort of human annotators.
Techniques
Our computer vision systems employ deep learning models such as Convolutional Neural Networks (CNNs) and Fully Convolutional Networks (FCNs) to divide an image into multiple segments, then identify and delineate distinct objects and boundaries within the image. These models are trained on large datasets with annotated images to recognise shapes, sizes, and types of objects – resulting in precise, pixel-level classification. This technique is crucial in applications where objects must be localised and boundaries are critical – like medical imaging, autonomous driving, and satellite image analysis.
Segmentation
Accurately identify and isolate objects or patterns within images and videos. Enable swift analysis, processing and extraction of valuable insights and data with precision and speed.
Techniques
Our computer vision systems employ deep learning models such as Convolutional Neural Networks (CNNs) and Fully Convolutional Networks (FCNs) to divide an image into multiple segments, then identify and delineate distinct objects and boundaries within the image. These models are trained on large datasets with annotated images to recognise shapes, sizes, and types of objects – resulting in precise, pixel-level classification. This technique is crucial in applications where objects must be localised and boundaries are critical – like medical imaging, autonomous driving, and satellite image analysis.
3D Reconstruction
Instantly create detailed 3D models from images and sensor data for applications like virtual reality, architectural visualisation, and precision manufacturing.
Techniques
Our 3D reconstruction technology creates accurate 3D models from 2D images by combining techniques like Structure from Motion (SfM) and Multi-View Stereo (MVS). SfM estimates camera positions and scene geometry, while MVS enhances detail by matching features across images. We also integrate LiDAR and photogrammetry for greater accuracy and detail, making our system perfect for virtual reality, architectural visualisation, and precision manufacturing.
Video and point clouds
Analyse and process 3D models, videos, and point cloud data to extract valuable insights. Enable applications like virtual reality, object recognition, and scene understanding.
Techniques
Our Video and Point Cloud processing solutions use advanced algorithms, specially designed to handle challenges related to the timing and positioning of moving scenes and 3D data. Our models, based on 3D CNNs and PointNet architectures, analyse video sequences for activity recognition and point clouds to classify objects and understand scenes. This involves dynamic object tracking, temporal segmentation, and 3D scene reconstruction – crucial for applications in video surveillance, motion capture, and 3D city modelling.
xAmplify is one of only two elite NVIDIA partners in Australia
We have the most experienced Artificial Intelligence Engineering practice in the country. We utilise NVIDIA’s world leading Omniverse platform, plus cuOpt (for route optimisation); Riva (for speech AI); and NeMo (for NLP).
Speak to our team of AI specialists
AI Ethics Principles at xAmplify
We’re committed to the responsible design, development, and deployment of artificial intelligence technologies, as outlined in our Ethics Principles Guide.