Moving Object Recognition Software

Moving Object Recognition Software


Moving Object Recognition Software AVADA-MEDIA

The capabilities of computer vision allow you to detect, recognize and track objects that are in motion. Experts are confident that in the near future, artificial intelligence (AI) will continue to improve and, thanks to its enormous potential, will be in demand in new industries.

The scope of application of software for recognizing moving objects is quite wide: from segmentation to identifying vehicles on the road. That is why the development of such software is already a priority task for many modern IT companies.

Moving Object Recognition Software

Application of neural networks in software for recognizing moving objects


Application of neural networks in software for recognizing moving objects AVADA-MEDIA

Neural networks function according to the principle of the nervous system of a living organism, including its ability for self-learning and further interpretation of information. Artificial intelligence receives a certain number of precedents (situations, objects, etc.), with each of which a clear set of data is associated. The more the database is provided to it, the faster the AI ​​learns to identify patterns, process information, classify objects, predict the consequences of events, etc.

In the digital age, the ability of artificial intelligence to track and analyze moving objects plays an important role. To automatically find and classify images, as well as to achieve the quality of human perception, neural networks undergo special training. For this purpose, open source software libraries such as Google’s TensorFlow can be used. The library includes various APIs for building deep learning architecture (such as CNN or RNN).

The capabilities of artificial intelligence are actively used in software development, including the design of software for recognizing moving objects. This technology is based on a computer vision technique that is customizable according to requirements and different use cases. For example, using neural network methods, you can filter out unnecessary objects from the tracker found and leave only those that are needed in a particular case (cars, people, etc.).

Neural networks are trained in three stages:

  • Statement of the problem of detecting and recognizing objects of a given type.
  • Formation of a “training kit” based on real data and model data.
  • Direct training of deep neural network detection algorithms.

To track and indicate the location of an object, the system creates bounding boxes around it (for this, the Object Detection function is used). After that, a certain part of the image is scanned for further classification and recognition.

The recognition process occurs simultaneously for a number of object characteristics: shape, size, color, etc. As the network continues to learn, when faced with new data, conceptual models for objects are expanded, refined and improved. Thus, the efficiency of AI is constantly increasing, which allows it to accurately solve increasingly complex problems.

To make sure that the software performs its functions and does not make mistakes, you can use a set of metrics that correspond to typical scenarios of using the system.

Advantages of developing software for recognition of moving objects at AVADA MEDIA


Advantages of developing software for recognition of moving objects at AVADA MEDIA AVADA-MEDIA

The AVADA MEDIA team is engaged in the design and implementation of software of any complexity, including software for recognizing moving objects based on neural networks. Our specialists have many years of experience and skills in working with innovative technologies, which they use in working on projects for various fields.

Deep neural networks have revolutionized computer vision and big data analysis. They provide visual pattern recognition results that are comparable or superior to human performance. The wide functionality of the technology guarantees a number of possibilities.

The range of applications of neural networks for recognizing moving objects is quite extensive, such systems can be used for:

  • personal identification;
  • big data analysis;
  • industrial safety and automation;
  • access control to objects;
  • video surveillance systems;
  • motion detection;
  • control of movement against a background of high noise levels, etc.

Algorithms of deep neural networks not only recognize, but also classify moving objects, calculate the speed and flow density (for example, when driving on the road), and detect objects in separate frames. At industrial enterprises, the system can control the quality of products, the correctness of the flow of technological processes, automate labor, etc.

Adding artificial intelligence to a business also has many benefits, including predicting a company’s performance in terms of revenue, operating income, and bottom line based on financial information and patents.

It should be noted that the effectiveness of a person’s performance of tasks largely depends on his experience, qualifications, fatigue and other factors. At the same time, a correctly configured system will always cope with work successfully, ensuring the required level of quality. Another plus of automation is performance, which is beyond the reach of humans.

AVADA MEDIA provides comprehensive services for the creation of custom software. We offer open communication at every stage, which makes the development process completely transparent and understandable for clients, allows for innovation and improves results. Our team consists of proactive and experienced professionals who select solutions in accordance with business priorities and project requirements.

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