The North American market for computer vision software has had a total investment of $120 million USD, while the Chinese market surged to $3.9 billion USD..Let’s take a look at the most promising and more intriguing technologies that make computer vision software development market grow so fast.Deep learning gained its popularity due to its supremacy in delivering accurate results.Traditional machine learning algorithms, as complex as they may be, are still very simple at their core..In the context of computer vision, this means identifying light and dark areas first, then categorizing lines, then shapes before moving towards a full picture recognition.Deep learning algorithms also perform better when you give them more data, which is not typical of machine learning algorithms..Not only has it allowed for many more pictures and videos to be used in training of deep learning algorithms, but it has also relieved a lot of work connected to annotating and labeling the data.The retail industry has been a pioneer in implementing computer vision software..Furthermore, edge computing can offset some of the costs of usage and maintenance of cloud computing for data sharing.For computer vision software, this means a possibility to respond even better in real time, and only move relevant insights to the cloud for further analysis..Replying on a cloud solution to analyze the data can be dangerous as latency can lead to accidents.A technology that has been used more frequently lately in object recognition and object tracking is point cloud..Some are even taking it a step further and combining it with AR equipment to get a sense of how their designs will look like in real life.Bio: Valeryia Shchutskaya is the Marketing Manager at InData Labs – a professional services firm delivering AI-powered software and technical solutions to companies who want to leverage data and machine learning algorithms for business value.Original.. More details