AI Image Recognition Market to Grow at a CAGR of 24.1% by 2023: Top Key Vendors - Amazon Web Services, Google, IBM Corporation, Intel Corporation, Micron Technology and More

AI Image Recognition Market Size
The AI image recognition market was valued at USD 1.13 billion in 2017 and is projected to reach a market value of USD 5.48 billion by 2023 at a CAGR of 24.1%, over the forecast period (2018 - 2023). The scope of the report includes insights on the solutions offered by major players including providers of hardware, software, services, and associated solutions. North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa regions are covered in the scope of this study. The study offers insights on various end user such as automotive, BFSI, healthcare, retail, security, etc.

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AI Image Recognition Market Positioning Analysis
Among the ten market players profiled for their presence in the global AI image recognition market, AWS, Google, IBM, Qualcomm, Microsoft, and Intel are the players who are among the top investor in R&D. AWS, in April 2018, has made their image recognition services available in new locations in Asia-Pacific, in Sydney. IBM already has begun implementing the usage of AI in image recognition and offers a stock of images to train the system.

Key Market Players Profiled
• Amazon Web Services (AWS), Inc.
• Google LLC
• IBM Corporation
• Intel Corporation
• Micron Technology Inc.
• Microsoft Corporation
• NVIDIA Corporation
• Qualcomm Corporation
• Samsung Electronics
• Xilinx, Inc.

Image Recognition and AI
Image recognition technologies comprise voice, iris, palm, hand vein pattern, fingerprints, retina, hand geometry, facial pattern recognition, object identification, etc. Image recognition based on these indications can be applied across various fields such as vehicular safety, advertising, security and surveillance, biometric scanning machines, pedestrian recognition, and e-commerce.
According to Eirik Thorsnes at UNI Research in Bergen, Norway, “There has been enormous development in the recent years, and we are now surpassing the human level regarding image recognition and analysis. Computers never get tired of looking and visualizing at near-identical images and may be capable of noticing even the tiniest nuances that we humans cannot see or may ignore. Also, as it gets easier to analyze large volumes of images and video, many processes in society can be improved and optimized,"
One such example is applying machine learning to the electronic medical record. An artificial intelligence analysis could help providers uncover patterns that identify disease subtypes, predict resistance to specific treatments or give a prognosis. With various sectors quickly understanding the impact of AI in image recognition tasks, organizations are now looking.

The Decline of Hardware Cost is Driving The AI Image Recognition Market
With declining costs of hardware, the infrastructure costs associated with development and deployment of technology have come down drastically. This is enabling companies to pursue the AI technology and develop solutions that cater industry-specific needs.
Smartphone makers account for almost one-third of global memory chip demand. Due to robust growth of smartphones and cloud services that require more powerful chips that can store more data, there has been a boom in the memory chip industry. With the introduction of AI focused chips and companies such as Facebook developing their hardware, which is expected to be available at moderate costs, the technology is expected to receive a boost in the market. Hardware manufacturers are also in the AI research race, for instance, in 2017 Intel invested approximately USD 1 billion in fueling product innovations

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Healthcare End User Vertical Segment is expected to Achieve Fastest Growth in the Forecast Period
In the next approaching 5 to 10 years, artificial intelligence is likely to fundamentally transform diagnostic imaging. This is expected to help in meeting the rising demand for imaging examinations, prevent diagnostic errors, and enable sustained productivity increases. There are several factors simultaneously driving integration of AI in radiology.
For example, the radiology consultant workforce in England went up to 5% between 2012 and 2015, while in the same period the count of CT and MR scans increased by 29% and 26%, respectively. This extreme gap between supply and demand has led to excessive work pressure on the average radiologist who is expected to interpret an image every three to four seconds, for eight hours a day.
Being able to recognize patterns at large scales has immense interdisciplinary value. Oncologists have trained machine learning systems on images of breast cancer cells so that they can spot the disease during its early stages. Images are more than pictures; they are data points that can be interpreted to gain insight into the patient’s behavior and health patterns, which are of ultimate importance in the healthcare sector. However, this transformation requires automated procedures, at least some of which will come under the field of AI.

Hardware Segment is projected to be the Second Largest regarding Revenue in segmentation by Type
Hardware refers to cameras, custom AI processors, memory devices, and advanced computational systems that are required for the working of AI image recognition tools. Hardware is one of the critical components of this technology, with most of the traditional computation infrastructure being non-reliable for AI applications. While AI image recognition can use existing technologies, limited capabilities and performance issues are pushing companies to pursue AI-focused hardware development.
Companies in the AI market have already developed custom chips for AI, with Google and Amazon announcing beta testing for their tools; and companies, such as Apple and Facebook, looking to build their own AI chips. Apart from AI chips, computational devices designed for AI image recognition and custom cameras focused on aiding AI systems are expected to witness increased demand over the forecast period. It is estimated that around USD 1.5 billion was invested in AI chip startups in 2017.
Currently, Europe is the Second Biggest Market regarding Revenue and is Expected to be overtaken by Asia-Pacific by the End of Forecast Period.
Startups in east Europe are leading in the development and adoption of AI-based solutions, and hence, the image recognition market is expected to be dominant in eastern Europe. As per the report of Asgard Capital Verwaltung GmbH, 2017, there were around 27 European artificial intelligence industry segments, deploying image recognition technologies.
Recently, about 25 European countries signed a deal to form a ‘European approach’ to artificial intelligence, to compete with the American and Asian tech giants. Representatives made a pact to work together on some of the most critical issues raised by AI related research, deployment, and social, economic, ethical, and legal questions. This development is expected to provide a necessary push to the region for the development and implementation of Al-based solutions, which, in turn, provide the needed booster in image recognition.

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This release was published on openPR.