Michael Abramov

Computer vision based AI models are transforming the online shopping experience. Companies, like Amazon and eBay, that facilitate consumer to consumer selling amass enormous online inventories, featuring billions of individual listings. A consequence of the ever increasing size of online shopping catalogues is increasing complexity for consumers. Finding the right

The management of waste is an often unseen but essential task that ensures our communities, businesses and hospitals can function safely. Sorting, extracting and disposing of waste is a difficult and dirty job that can expose workers to potentially dangerous substances. Computer vision based AI models are beginning to be

Bias in training data for computer vision AI can lead to models that perform poorly in the real world and can even leave companies open to charges of discrimination. This is particularly important in a public facing industry like retail. AI has the potential to transform many aspects of in-store

Annotated video training data plays an important role in the development of computer vision based AI models for robotics applications. By labeling each frame of video training data annotators create vital contextual information that allows AI systems to function effectively on busy production lines and in crowded warehouses. Video annotation

Security systems powered by computer vision based AI models have the potential to make public spaces safer and private property more secure. By automating aspects of security monitoring, AI equipped cameras act as a force multiplier for security staff, ensuring that effective surveillance is in place at all times. However,

Most image and video training data for machine learning is collected from large open sources like Imagenet. These online repositories allow developers to assemble large pools of data that can then be annotated with labels and categories, creating functional datasets that power computer vision based applications. Whilst data collection resources