Computer Vision

Due to advances in the field of machine learning in recent years, any pattern in image data visible to the human eye can also be made visible to a machine. Sometimes machines can even be trained to detect structures not visible to humans.

Criteria to discover Computer Vision projects

Criteria to discover attractive process automation projects, where visual information plays a crucial role:

Currently the process is cost-intensive and/or a faster decision creates substantial value

A (trained) human could make a good decision mainly based on visual information

There is enough data available (as a rule of thumb: 200 - 2.000 images. This, of course, is highly dependent on the use-case)

In our experience, only by combining knowhow of internal operations with machine vision expertise, projects can be framed well. Feel free to approach us with questions, especially whether we deem your project to be technically feasible.

Our process

1. Process

Together we discuss your process automation projects along three different dimensions: cost savings, strategic value and technical feasibility. After settling for a specific project, we put special emphasis on the needs of the end users.

2. Innovative

We are an experienced team of machine learners. Our algorithms find complicated patterns in unstructured, mostly visual and text data. Once detected, these patterns are the basis for the automation of the underlying process.

3. Decision-support

We make a point of integrating our customers in the project's code repository as well as in weekly progress meetings. Agility, clean code and a modular program structure help us to deliver easy-to-maintain software, that simply works.

Case Studies in Computer Vision

Includes live demo

Automatic planning of solar systems

Our client is a company from the solar sector, which offers the planning, consultation and installation of solar systems for private households. The aim of this project is to automate the planning process of solar systems. Specifically, this involves preparing an individual offer for customers so that they can estimate the costs and benefits of the investment and get an aesthetic impression of the final result.
Includes live demo

Convective clouds detection

Our client here is Deutscher Wetterdienst (DWD). Part of their responsibility is to prepare weather reports for pilots in a system called METAR. We had been tasked with creating a model to assist the detection of convective clouds using satellite imagery to support other forms of detection.

Use Cases in Computer Vision

Analysis of handwritten documents

Handwritten documents can be read out and prefilled using machine learning algorithms. By further...

Analysis of X-Ray/MRI images

Diagnostic suggestions can be made by analyzing X-ray or MRI images using an algorithm.

Automatic land register update

Authorities need up-to-date information on the use of their land to be able to plan public...

Automatic object detection on airport runways

Runways are controlled by air traffic controllers observing the runways from the tower. As this...

Classification into quality classes

Through standardized images of different leathers, a machine learning algorithm can classify...

Classification of equipment damage

Photos of defective spare parts are analyzed by a machine learning algorithm and the damage is...

Determining the price of a building insurance

The optimum price of a building insurance can be determined by the customer specifying the...

Early classification of crop types

Crop Classification is a highly relevant topic in agriculture for farmers, authorities and...

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