Computer vision software development

We are an IT outsourcing company specializing in fintech, blockchain outsource software development, outstaff developers, and tech consulting. With much expertise in the outsource software development for the computer vision industry and a lot of understanding of this field we can transform your business and propel it to the next level. For over five years we have been creating specialized software for the real estate owners, builders, banks, investors, developers, architects, and leasing companies.
Cooperate
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The reasons for software solutions’ application in the computer vision industry

01.

A limitation to the use of systems based on computer vision is to overcome a certain threshold of utility, in other words, the system must meet a set of requirements for performance parameters.

02.

Practical implementation of computer vision systems is limited by the characteristics of the modern element base, namely: the characteristics of video cameras, other sensors (radars, lidars, etc.), as well as the characteristics of computing processors on which subprograms of computer vision systems are executed.

03.

Inability to quickly and accurately classify and recognize images from CV systems.

04.

Mathematical and algorithmic support of computer vision in "understanding" or recognition of the analyzed scenes, even without taking into account the problems of collecting the initial visual data and without restrictions on the processing time, is a difficult task.

01.

A limitation to the use of systems based on computer vision is to overcome a certain threshold of utility, in other words, the system must meet a set of requirements for performance parameters.

02.

Practical implementation of computer vision systems is limited by the characteristics of the modern element base, namely: the characteristics of video cameras, other sensors (radars, lidars, etc.), as well as the characteristics of computing processors on which subprograms of computer vision systems are executed.

03.

Inability to quickly and accurately classify and recognize images from CV systems.

04.

Mathematical and algorithmic support of computer vision in "understanding" or recognition of the analyzed scenes, even without taking into account the problems of collecting the initial visual data and without restrictions on the processing time, is a difficult task.

Application of blockchain technologies in the computer vision industry

Blockchain is a foundational technology that is revolutionizing the way transactions are conceived, executed, managed, and monetized. While the commercial benefits of blockchain infrastructure are imminent, the underlying technological problems need significant attention from researchers. Of specific interest to researchers and application developers in computer vision is the tremendous opportunity to make a connection to these emerging infrastructure capabilities and realize how their skills can be leveraged to make an impact by marrying computer vision and blockchain technologies. This marriage can happen in two ways. Firstly, computer vision technologies can be exploited to address critical gaps in blockchain platforms such as scaling, modeling, and privacy analysis. Secondly, as the world moves towards increasing decentralization of AI and emergence of new AI and computer vision marketplaces, a blockchain-based infrastructure would be essential to create the necessary trust between diverse stakeholders.

Many complex practical challenges such as stakeholder identity management, compliance with regulations, integrity of data, and protecting privacy of the sensitive information can be effectively addressed using blockchain technology. As cameras become ubiquitous (over 4 billion mobile phones, millions of public surveillance cameras, and increasing presence of egocentric bodycams in professional environments) and compute power is becoming pervasively available, it is increasingly clear that the business world is going to consider camera as the default sensor and camera-based analytics as the de facto information channel to improve the integrity of transactions from various diverse perspectives.

Software development services for the computer vision industry

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Unified development environment

Enables the development of peripheral AI and computer vision applications running on a variety of hardware types.

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Software Hub

Allows you to quickly search, prototype and integrate the required edge computing software.

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SDK

With one API, you can leverage hardware acceleration for fast video transcoding, image processing and media workflows across all hardware.

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DevCloud

Allows you to streamline prototyping and benchmarking using the cloud sandbox.

Computer vision industry software development benefits from Boosty Labs

Enhancing Business Resilience with Computer Vision

Companies and industries around the world are having to adapt to the changes caused by the pandemic, as well as the growing demand for video technology.

Using computer vision to meet increased demand

As our world becomes more complex, the use of computer vision can help organizations expand their capabilities and remain competitive.

Computer vision helps industries innovate and sustainability in the aftermath of the COVID-19 pandemic

Using computer vision, companies provide a safe environment for employees and customers, and improve their operations with technology.

Digitalization trends in the computer vision industry

An impressive breakthrough occurred in the field of object recognition: over the past five years, the fundamentals of learning neural networks and architectural solutions have improved (in terms of hardware); there has been a noticeable shift in the accuracy of object recognition on open data sets – from 70 to 98% accuracy.

Neural networks work better with many tasks now than people (not more precisely, but without fatigue and the need to sometimes distract from a routine task). Although, until now, we cannot improve the accuracy of the result of a person's work, obtained with the help of ordinary, non-computer vision (for example, when viewing thermal maps by a specialist or CT scans by a doctor).

The forecasts are optimistic: the market is growing and, according to experts, in the next 5 years it is expected to expand by another 1,5 times. When asked about the fields of application of computer vision, one can answer that it can be used wherever there are any images.

The most active consumers of this technology today are retail, manufacturing and medicine. Somewhere computer vision helps to assess the actions of employees, somewhere it fights against fraud, and somewhere it controls quality and warehouses.

The very specifics of the industry and the transition to open layouts are forcing retailers to install as many cameras as possible to fight those who spoil or try to steal goods. From the point of view of a dataset, retail is the most suitable area where it is necessary not only to record data, but also to store it.

Another area where computer vision technologies are often applied is manufacturing. They are primarily used to automate routine actions, especially in the field of defect recognition directly on the conveyor or for evaluation immediately after production.

In medicine, we are dealing with the automation of routine processes that do not require the attention of a doctor, but require triage of patients. In addition, machine learning and image analysis are actively used to automate manual markup.

Every year we get new proposals for the fields of application of image or video recognition. By our very nature, we rely very heavily on what we see. And we strive to visualize information in order to be able to understand a topic or solve a problem. For example, data scientists draw a lot of graphs when analyzing data, because they often make it easier to recognize some feature or problem in the data.

From the side of computer vision, the situation is very similar: now it is successfully used in cases related to the recognition of sounds, signals from seismometers and other sensors, in the analysis of geo-sections and in other areas of geological exploration. All those cases when you need to contact an expert for comments on an image are potentially suitable for the use of computer vision in order to speed up and simplify interpretation.