Market research report published by MarektsandMarkets "AI in Computer Vision Market analyzes the AI in Computer Vision Market by Component (Hardware, Software), Vertical (Automotive, Sports & Entertainment, Consumer, Robotics & Machine Vision, Healthcare, Security & Surveillance, Agriculture), and Region - Global Forecast to 2023", the AI in computer vision market is expected to be valued at USD 3.62 Billion in 2018 and is expected to reach USD 25.32 Billion by 2023, at a CAGR of 47.54% between 2018 and 2023.
The increasing demand for computer vision systems in non-traditional and emerging applications and growing demand for edge computing in mobile devices are among the factors driving the growth of the market.
With the increasing labor cost in the security market and use of robotics in the healthcare industry, AI-based computer vision systems are being used for many applications. The market for AI-enabled computer vision has an increasing demand in various emerging applications such as unmanned aerial vehicles, augmented reality, missile guidance, autonomous vehicles, and others.
Hardware expected to grow at a high rate during the forecast period
The key factor driving the growth of hardware in the AI based computer vision market is the growing penetration of AI-capable processors in mobile devices, such as smartphones, drones, automotive, and consumer electronics devices.
Consumer vertical expected to hold the largest share during the forecast period
Key factors contributing to the growth of the AI in computer vision market in the consumer vertical is the addition of AI capabilities to smartphones, which will help change mainly 2 aspects: user–machine interaction and context-personalized openness. User machine interaction will improve the efficiencies between the user and their phone across text, voice, image, video, and sensors, whereas the latter will actively provide services and aggregated information across apps, content, third-party features, and native features.
For More Information - https://www.marketsandmarkets.com/Market-Reports/ai-in-computer-vision-market-141658064.html
AI in computer vision market in North America expected to hold the largest share in 2017
North America is expected to hold the largest market share in 2017. Startups in the US are receiving funds from various organizations to imply the AI technology in autonomous drones and other flying vehicles. The major focus is to overcome challenges faced by industrial drones in terms of reliability, safety, and autonomy. Thus, companies have come up with solutions that combine computer vision and deep learning algorithms and identify potential hazards, and speed and distance. The market for AI in computer vision in APAC is expected to grow at the highest CAGR during the forecast period and surpass North America by 2023. Finisar (US), Lumentum (US), Broadcom (US), Sumitomo Electric (Japan), and Accelink Technologies (China) are the leading players in the AI in Computer Vision Market.
Major players operating in the AI in computer vision market include
NVIDIA (US), Intel (US), Qualcomm (US), Apple (US), Alphabet (US), Microsoft (US), Facebook (US), Wikitude (Austria), Xilinx (California), Basler (Germany), Teledyne Technologies (US), Cognex (US), General Electric (US), and Avigilon (Canada).
Top 2 players in the AI in computer vision market:
NVIDIA
NVIDIA is among the world leaders in the visual computing business. It has a well-established geographic footprint and deals with major OEMs or ODMs. The company continues to lead in the development of new products for the AI in computer vision market. Recently, NVIDIA has witnessed significant jump in its data center revenue. It is giving tough competition to Intel in the data center market. NVIDIA DRIVE for automakers to build and deploy self-driving cars and trucks that are functionally safe and certified to international safety standards is one of the important products of the company. For instance, in January 2018, NVIDIA announced a new architecture of NVIDIA DRIVE, its AI autonomous vehicle platform that uses redundant and diverse functions to enable vehicles to operate safely.
Intel
Intel designs, manufactures, and sells computer, networking, and communication platforms globally. It develops computer vision and machine learning-based sensing products, mapping and driving policy technology solutions for advanced driver assistance systems, and autonomous driving technologies. In the AI-based computer vision market, the company focused on inorganic strategies such as acquisitions and partnerships between 2016 and 2017. For instance, in August 2017, Intel acquired Mobileye (Israel) to develop automated cloud-to-car solutions.
About MarketsandMarkets™
MarketsandMarkets™ provides quantified B2B research on 30,000 high growth niche opportunities/threats which will impact 70% to 80% of worldwide companies’ revenues. Currently servicing 7500 customers worldwide including 80% of global Fortune 1000 companies as clients. Almost 75,000 top officers across eight industries worldwide approach MarketsandMarkets™ for their painpoints around revenues decisions.
Our 850 fulltime analyst and SMEs at MarketsandMarkets™ are tracking global high growth markets following the “Growth Engagement Model – GEM”. The GEM aims at proactive collaboration with the clients to identify new opportunities, identify most important customers, write “Attack, avoid and defend” strategies, identify sources of incremental revenues for both the company and its competitors. MarketsandMarkets™ now coming up with 1,500 MicroQuadrants (Positioning top players across leaders, emerging companies, innovators, strategic players) annually in high growth emerging segments. MarketsandMarkets™ is determined to benefit more than 10,000 companies this year for their revenue planning and help them take their innovations/disruptions early to the market by providing them research ahead of the curve.
MarketsandMarkets’s flagship competitive intelligence and market research platform, “Knowledge Store” connects over 200,000 markets and entire value chains for deeper understanding of the unmet insights along with market sizing and forecasts of niche markets.
Contact:
Mr. Shelly Singh
MarketsandMarkets™ INC.
630 Dundee Road
Suite 430
Northbrook, IL 60062
USA : 1-888-600-6441
Email: [email protected]
Visit Our Website: https://www.marketsandmarkets.com
Especially amid movement restrictions induced by the COVID-19 pandemic, research shows that global online sales jumped to $26.7 trillion in 2020.
With the rise of ecommerce, one thing is abundantly clear: brick-and-mortar retailers need to innovate if they want to stay competitive.
Among the most promising applications of computer vision include inventory management, loss prevention, automated checkout, and behavioral analytics.
The company holds 23 patents on its technology and can analyze images from phones, in-store cameras, and grocery store robots.Trax uses computer vision technology to scan shelves in stores and identify what is neededAutomated checkoutStandard.ai: Previously known as Standard Cognition, Standard.ai’s automated checkout solution is made to fit with retailers’ existing stores and technology.
Standard doesn't use any facial recognition or biometrics, and all deployments are on-premise to ensure maximum performance and security for retailers and shoppers alike.Trigo: Using proprietary algorithms and affordable off-the-shelf sensor kits, Tel Aviv-based Trigo allows retailers to analyze anonymized shoppers’ movements and product choices in real time.
Once a customer reaches a certain threshold, the system sends an alert, along relevant video clips, to the appropriate staff member.Clips from the VaakEye product demo videoBehavioral analyticsDeep North: Deep North provides an analytics platform that builds real-time video intelligence for retailers based on video data from CCTV and other cameras that those retailers already use.
For many decades, scientists have been able to quantify the order of amino acids accurately, but accurately estimating the form of a protein has always been a challenging task.If we can decode the sequence of amino acids in a protein structure and determine the form of a protein accurately, it will provide many functions.Accurate assessment of protein structure is beneficial in understanding the biological evolution of a particular protein and also helps to understand what kind of diseases it causes and what protection it can provide against other diseases.In particular, an accurate assessment of the structure of a protein is crucial to understanding the function of proteins and cells and how they can function and cause disease, and this understanding is also beneficial for the development of treatment and vaccines.Now, if you look at SARS-CoV-2, it is the spike protein structure of the virus that attaches to the AS2 receptor in our cells, causing infection.
We were able to develop this understanding very quickly, mainly due to the progress we have made regarding our performance and assessment of protein structures.First DiscoverySee, this field began to develop many decades ago, and in 1972, Christian B. Unfinsen, a scientist, predicted that by accurately calculating the order of amino acids, we could reduce protein formation.
So this discovery won him the Nobel Prize in Chemistry, and it laid the foundation for the analysis and evaluation of protein structures.X-ray crystallographyAbout 60 years ago, a scientist named Max Perutz began to evaluate protein structures using experiments.
He used X-ray crystallography to determine the exact form of myoglobin and haemoglobin, and this discovery helped us to understand the proper function of haemoglobin in the blood, which transports oxygen from the lungs to the tissues and cells of the lungs.
This understanding of the structure of myoglobin and haemoglobin has helped us to understand how a change in a single amino acid can lead to diseases such as sickle cell anaemia.Genome sequencingToday, decoding the sequence of amino acids and completing the line more accurately is even more advanced, thanks to advances in the genetic series.
Because at the end of the day, the protein structures in the amino acids are essentially a part of the gene and the rapid advances we have made in the gene sequence have helped us to calculate the order of the amino acids easily.
Open data is fueling commercial and technological advancement in autonomous driving—one of most well known resources being the nuScenes dataset.Developed by the team at Motional (formerly nuTonomy), nuScenes is one of the most popular open-source datasets for autonomous driving.
The nuScenes dataset enables researchers to study a wide range of urban driving situations using data captured by the full sensor suite of a self-driving car.
Recorded in Boston and Singapore, nuScenes features a diverse range of traffic situations, driving maneuvers, and unexpected behaviors.The dataset includes:Full sensor suite: 32-beam LiDAR, 6 cameras and radars with complete 360° coverage1000 urban street scenes, 20 seconds each1,440,000 camera images23 classes and 8 attributesAccessing nuScenes data in SiaSearchTo access the data yourself, you’ll need to sign up for a free account on SiaSearch.
This view lets you quickly understand the overall dataset composition, as well as identify any gaps in data distribution.Querying the nuScenes DatasetHaving a holistic view of the dataset, while useful, is not enough.
The ability to drill into specific subsets can uncover insights and imbalances in the data—a critical step in model building and validation.SiaSearch makes every piece of nuScenes data searchable against all available and auto-extracted dimensions using its intelligent search interface.
The platform features two ways to search for the exact sequences you want, using either a visual or code interface.
Colon cancer is a typical cancer that begins in the colon which is called as large intestine.
Colon is the final part of the digestive tract.Artificial Intelligence can predict Bowel Cancer
