The massive digitalization of companies over the past 20 years has not benefited field operations very much. Today, Computer Vision allows the digitisation of processes in the physical world thanks to the visual analysis of field situations and the automatic feedback of information. At Deepomatic, we call it Visual Automation.
In this white paper, you will discover:
It is becoming increasingly more difficult to control the numerous everyday field interventions. Provide your field service technicians with a computer vision app to guide and control their real-time interventions.
In this white paper you will learn how to:
Deepomatic « est la meilleure offre pour développer une solution sur mesure de Computer Vision pour le monde physique. »
Le rapport de Forrester Research inclut 11 des plus importants fournisseurs de plateformes de Computer Vision et les évalue en fonction de 10 critères allant de la vision d’entreprise et de son approche marché à l’aspect fonctionnel de son produit. Deepomatic a été reconnu comme un » Strong Performer « , grâce à une note différenciante sur les critères de facilité d’utilisation, de vision et de roadmap, ainsi qu’une une note dite “de performance comparable” sur six autres critères.
Dans ce rapport, vous découvrirez :
Over the last few years, the number of visual tasks solved by deep learning has grown exponentially. However, this technology still fails to achieve results in the industrial world. We propose a new framework, called Lean AI, that minimizes the risks of failure as well as maximizes the performance of AI systems.
In this white paper, you will learn:
The development & fundamentals of the Lean AI framework
The challenges associated with implementing Lean AI methodology
There are more than one million video surveillance cameras in France – it is a great opportunity to increase the safety and security of operating sites.
In this white paper you will discover:
Whether it is safety on the construction site, manual monitoring often subject to errors, or the theft of materials and equipment: the construction industry faces many challenges. While only 50% of companies in the sector have established a technological roadmap, image recognition can provide concrete and rapid solutions.
In this mini white paper, you will learn:
54 billion euros are invested in R&D by car manufacturers in areas such as the development of self-driving cars or the automation of production lines and quality control. Video recognition is the technology to invest in for innovation in the sector.
In this white paper, you will learn:
The constant increase in the price of oil is driving companies in the sector to innovate in order to reduce operating costs and improve productivity in their exploration activities. 89% of oil companies are already taking digitization initiatives.
In this mini white paper, you will learn:
The pharmaceutical industry is under strong pressure to ensure the reliability of its drugs and production processes: safety and hygiene, laboratory tests, or even fraud: video recognition is a technological lever for companies in the sector to restore public confidence.
In this mini white paper, you will learn:
Public transport is at the heart of safety and environmental issues. By integrating video recognition into their activities, operators can improve the experience of their users and invent the modes of transportation of tomorrow.
In this mini white paper, you will learn:
The rise of e-commerce is driving retailers to rethink the customer experience in physical stores and find solutions to waiting lines and other customer frustrations. Image recognition is emerging as one of the technologies providing many solutions to this sector, such as self checkout systems.
In this mini white paper, you will learn:
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