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 evaluation

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 solutions

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 software

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.

Projects in Computer Vision

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Automatic Planning of Solar Systems

Using machine learning, computer vision and object recognition, dida succeeded in developing a software to automatically plan solar based on satellite data.

Artisanal and Small Mine Detection

Machine learning and environmental protection: Development of software for automated detection of illegal small-scale mining using satellite data.

Defect Detection in Manufacturing

AI-supported optical defect detection for semiconductor laser production

Convective Clouds Detection

Machine learning in remote sensing: Read here about our project with the DWD and the object detection of convective clouds using deep learning.

Crop Type Classification

Machine learning and remote sensing: The computer vision software developed by dida enables predictions for innovative agriculture.

Monitoring Urban Growth and Change

We as an AI software provider developed, with the help of computer vision, an algorithm for monitoring & predicting urban change.

Predicting Potential Reach of Video Ad Campaigns

As an AI-IT software provider, we designed software for Ströer that provides accurate simulations to predict the performance of advertising campaigns.

Smart Access Control with Facial Recognition

Machine learning and security systems: Development of a multi-level system with facial recognition and automated access control using AI.

Blog Posts in Computer Vision

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Computer Vision

Early Classification of Crop Fields through Satellite Image Time Series

By Tiago Sanona April 3rd, 2023

We explain a deep learning-based algorithm for the classification of crop types from satellite time series data which is based on the transformer architecture.


Leveraging Machine Learning for Environmental Protection

By Edit Szügyi March 14th, 2023

Protecting the natural environment is arguably the biggest challenge of our generation. I show how and where Machine Learning can help.

Computer Vision

An Introduction to Metric Learning

By William Clemens (PhD) September 26th, 2022

Introduction to metric learning: Expand your knowledge of metric learning, common distance measures & loss functions such as the triplet loss.


Recommendation systems - an overview

By Konrad Mundinger August 29th, 2022

Expand your knowledge about recommender systems: Explanation & application and examples, as well as info about collaborative & content-based filtering here.

Computer Vision

The best (Python) tools for remote sensing

By Emilius Richter August 2nd, 2022

Python tools for remote sensing using machine learning: Comparison of Python software for data retrieval and processing of satellite data read here.

Computer Vision

Image Captioning with Attention

By Madina Kasymova May 31st, 2022

An application of deep learning: Read here about image labeling algorithms & an approach to image labeling - the attention mechanism.

Computer Vision

How to implement a labeling tool for image classification in a Jupyter notebook

By • March 21st, 2022

Read here how to get a labeling tool for image classification working in a Jupyter notebook & what options there are for extending it.

Computer Vision

Data-centric Machine Learning: Making customized ML solutions production-ready

By David Berscheid October 6th, 2021

Read here about model- and data-centric machine learning & how we at dida improve machine learning projects by using data-centric techniques.

Use Cases in Computer Vision

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Webinars in Computer Vision

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