AI in the European market is estimated to rise from US$10.1 billion in 2018 to US$20.0 billion in 2023 with a 9.2% CAGR over the projected years of 2018-2023. Government funding to develop and promote artificial intelligence is fuelling the market growth in this region. The AI market in Europe is segmented by technology and industry vertical. The various technologies are sub-divided into machine learning, natural language processing, image processing, and speech recognition. Based on industry verticals, the market is categorized into media and advertising, retail, telecom and IT, healthcare, automotive and transportation, and others (agriculture, law, educational institutions).
The artificial intelligence market in Europe has extended its branches in areas like semiconductor, healthcare, industrial and automotive transportation. Government funding to develop and promote artificial intelligence is a major influencing factor for the European Artificial Intelligence market's progress. The U.K market was a significant contributor to AI in this region. The U.K government has pledged significant funding to develop machine learning and robotics at universities. The country has also experienced a rise in the number of start-ups, which collectively contributed nearly half a million to conduct machine learning research.
Furthermore, progress in deep learning and Artificial Neural Networks (ANN) has also fuelled the adoption of AI in several industries, such as aerospace, healthcare, manufacturing, and automotive. ANN is substituting conventional machine learning systems to evolve precise and accurate versions. For instance, recent advancements in computer vision technology, such as Generative Adversarial Networks (GAN) and Single Shot Multi-Box Detector (SSD), have led to digital image processing techniques. For instance, images and videos which are taken in low light or low resolution can be transformed into HD quality by employing these techniques. The continuous research in computer vision has built the foundation for digital image processing in security and surveillance, healthcare, and transportation, among other sectors. Such emerging machine learning methods are anticipated to alter the manner AI versions are trained and deployed.
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