Artificial Intelligence

Object detection involves identifying instances of real-world objects such as faces, vehicles, or animals in digital images and videos. This is typically achieved using deep learning models like Convolutional Neural Networks (CNNs).

Image classification assigns a label to an entire image or photograph. This process, often using CNNs, categorises images into predefined classes.

This involves identifying or verifying a person's identity using their face, employing techniques like Eigenfaces, Fisherfaces, or deep learning approaches.

Image segmentation partitions an image into multiple segments to simplify or change its representation. Techniques include thresholding, clustering methods, and CNNs.

This involves tracking the movement of objects or individuals over time in videos. Methods include point tracking, kernel tracking, and silhouette tracking.

3D image processing deals with processing images that have depth data, using techniques like stereoscopic vision, structure from motion, and depth sensing.

Processing and analysing video data in real-time, using frame differencing, optical flow, and real-time CNNs.

Developing tailored AI models to meet specific client needs in image processing and analysis.

Identifying patterns and regularities in data using statistical analysis, machine learning, and neural networks.