Turbologo neural network

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Turbologo
This product is a completely Russian development. The neural network will independently, without resorting to the services of a design studio, develop a logo on request. When creating it, the algorithm takes into account your preferences in color, style, etc. The neural network has the same operating principle as others. To launch a project, you need to specify the name of the organization, slogan, and field of activity. After some time, a large number of options are available to the user, you need to choose the one you like.


As for the cost, you can generate an unlimited number of options absolutely free of charge, but you will have to pay a little for downloading materials. There are three tariffs to nursing homes email list choose from, the most affordable of which is 790 rubles for three months of use.

Nikolay Ironov - designer and neural network
Nikolay Ironov is an exclusive project created by Artemy Lebedev Studio. The team of developers managed artificial intelligence for a year, and all users believed that the works were created by real designers. The platform independently creates logos, while the result is not discussed with the customer. Not everyone likes this approach to work. The program works strictly in accordance with the conditional technical map.

The standard tariff costs 19,900 rubles per month, and the promo tariff costs 29,900 rubles.

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Dmitry Svistunov
Head of SEO and Development
Read more posts on my personal blog:

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Neural networks for object detection and tracking
Object Detection or object detection and detection is the detection of objects in a picture or frame. It can be applied to one or several objects with different parameters. Example: these can be trucks or cars, only blue vehicles, cars with special coloring. Thus, the neural network determines the position around the object and sends its bounding boxes to the program. The key point of the task is that the data in the photo or video is not marked in any way. For the program, this is just a multi-colored set of pixels. As a result, the user receives the coordinates of the objects, as well as their estimated boundaries.

Object Tracking is a more complex task, since it is not enough to identify objects in a frame, it is also necessary to link information from previous frames so that what was found is not lost. Example: when analyzing a recording of several athletes running, it is quite difficult to distinguish one from another, since people in the video can overlap each other from time to time. With the help of Object Tracking, it becomes possible to effectively solve problems of this kind by detecting an object at the very beginning of a video sequence and tracking it further by some one parameter, for example, a red T-shirt or a green armband.

Currently, object recognition is a fairly popular operation in solving a wide range of problems. Below are the most popular neural networks of 2023, which are designed to identify and track objects.