Computer Vision Engineer jobs

Find jobs in Computer Vision

Machine learning and neural networks can teach a computer to notice defects and problems before they affect production. Computer Vision is a field of artificial intelligence that studies methods and algorithms for interpreting and analyzing images and videos. Goal: to teach a computer to find, see and understand images, as a person does.

What is computer vision?

The first work in computer vision engineer jobs search of a method for teaching machines to understand visual data began in 1959. Then came the Huberman-Weiskrantz experiment: researchers showed a cat a set of images on a screen and measured the electrical activity of its visual cortex using electrodes on its head. The results of the experiment showed that the visual cortex begins image processing by detecting simple shapes such as lines and contours. An ultra-precise neural network (CNN) works on the same principle. It starts by examining the basic features of the image, such as hard edges and shapes. It then uses this knowledge to fill in more detailed information about the image in a process of iterative prediction.

Areas of application of computer vision

You can find computer vision both in contract jobs and in remote jobs, for example:

1.    Automatic recognition of license plates on the roads. It is used, for example, in paid parking management systems, in speed cameras to identify and record license plates of violators.

2.    Face recognition. Technology is needed in various contexts, for example, to access a mobile phone, allow a limited number of people into a building, search for criminals or missing people.

3.    Medical diagnostics. A properly trained computer will detect pathologies in ultrasound and MRI images faster and more accurately than a human, warn about skin changes that may be a sign of disease, and identify signs of Alzheimer’s using MRI of the brain.

4.    Quality control. For example, a computer can be tasked with quality control on a production line, identifying defects, and rejecting faulty products. This allows you to reduce costs and increase production efficiency, as well as reduce the number of defects and improve product quality.

5.    Automatic sorting. Computer vision is used in AI jobs industry to sort products based on their characteristics and quality, reducing errors and increasing productivity.

6.    Unmanned transport. Before a driverless car is released onto the road, it must be taught to drive safely for pedestrians and other vehicles. To do this, the computer must be able to recognize objects around and know what to do in a given case.

7.    Improving the lives of people with disabilities. Computer vision is used to create special devices: “smart cameras”, “smart glasses”. They are used for reading, pattern recognition, city navigation, and gathering information from the real world in real time.

Besides this, there are many more examples.

How is it used in data collection for machine learning?

Computer vision is used to create datasets that consist of images, videos, and other types of multimedia data, so there are needed computer vision vacancies.

One example of using computer vision positions to collect data is creating a dataset with images of people. To do this, you can use a camera and computer vision algorithms to take images and overlay annotations on them that mark the boundaries of the face and facial expressions. This dataset can then be used to train a face recognition model.

Another example is the use of computer vision to create a dataset with images of products in a supermarket. An automated system can take photos of every product in a store and use computer vision algorithms to create labels that indicate the product's name and price. Next, based on the data received, an AI/ML model is trained, which will be able to recognize best products on store shelves in the best companies and track their quantity and price.

Conclusion

So, computer vision vacancy is an interdisciplinary scientific field whose goal is to create and study computer systems that have a common high-level understanding of digital images or videos. From a practical perspective, computer vision seeks to understand and automate tasks that the human visual system can perform. In machine learning, computer vision software developer is implemented using convolutional neural networks (CNN) to solve problems of segmentation, classification, detection, and image processing!