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In the era of internet shopping brick and mortar stalls still have an appeal for many shoppers. Many consumers still enjoy browsing through physical products and comparing in-store deals to find the best bargains. Food sellers and clothing stores are the primary focus of in-store shopping and in-both sectors companies

Computer vision based AI models are required to interpret and operate within a complex world, filled with difference and variety. As a result machine learning algorithms need to be trained with image and video data that reflects a chaotic real world. Image and video datasets for machine learning need to

Managing traffic and transit can be a challenge for city governments. As cities grow so does vehicle congestion. As thousands of vehicles move through urban areas each day they also cause secondary issues. Namely, parking and parking enforcement. To deal with these emerging difficulties city governments are turning to computer

AI can keep businesses and public spaces safe. Computer vision models can take on the burden of security surveillance and ensure that camera systems are monitored 24/7. Developers in this sector are beginning to bring AI applications to market that can support security staff by giving advanced warning of

The COVID-19 pandemic has led to a supply chain crisis that is ongoing. Fluctuations  in demand, labour shortages and distribution delays have led to many products becoming harder to access for consumers. As a result many governments and companies are looking at ways to improve supply chain resilience and reliability

COVID-19 had led to changes in many industries. Many offices have moved to a remote working model, and supply chain stresses have impacted many businesses. In the agricultural sector the pandemic has led to a labour crisis. The industry has responded by looking to new technology for solutions. Computer vision

Data collection is a vital step in the machine learning for computer vision process. Before image and video annotation can take place, raw data needs to be assembled. This data needs to be of the quality, variety, and quantity required for functional training data. To achieve this developers often make