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Government & Public Sector

Accelerate civil services and relieve civil servants from monotonous tasks

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With Machine Learning, civil service operations can be optimized by:

automating simple, repetitive civil services completely
helping citizens to find and request the required service, e.g. by Chatbots or Question Answering
automating and updating sovereign duties and information services based on satellite imagery

Projects in Government & Public Sector

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Legal Review of Rental Contracts

Through dida's expertise in the field of natural language processing (NLP) we succeeded in creating a software for the legal review of rental agreements.

Automatic Checking of Service Charge Statements

With machine learning and NLP: Read about the development of software for the automatic verification of settlements using artificial intelligence.

Semantic Search for Public Administration

Machine learning and information extraction: dida's AI-based algorithm simplifies business registrations through intelligent semantic search.

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.

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 Government & Public Sector

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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.

Introductions

Project proposals - the first step to a successful ML project

By Emilius Richter July 18th, 2022

For a software provider, the project proposal is the first step toward meeting the needs of the customer. In this article, I will describe the most important modules in machine learning project proposals.

Introductions

Ethics in Natural Language Processing

By Marty Oelschläger (PhD) December 20th, 2021

Learn more about the ethics in natural language processing (NLP), the societal impact of machine learning (ML) & why caution should be exercised.

Natural Language Processing

GPT-3 and beyond - Part 2: Shortcomings and remedies

By Fabian Gringel October 24th, 2021

Expand your knowledge about GPT-3 and read here about opportunities, weaknesses & troubleshooting as well as alternatives of the AI-based language model.

Natural Language Processing

GPT-3 and beyond - Part 1: The basic recipe

By Fabian Gringel September 27th, 2021

Read here about how GPT-3 works, as well as its dangers & applications, and learn how you can try a GPT-3-like model for free.

Computer Vision

CLIP: Mining the treasure trove of unlabeled image data

By Fabian Gringel June 21st, 2021

Contrastive language image pretraining (CLIP): Read about the functionality as well as applications of the CLIP model, a zero-shot image classifier.

Computer Vision

Migrating labels from Planet Scope to Sentinel-2

By • June 4th, 2021

In this blog article, I want to briefly describe the process of migrating labels from Planet Scope to Sentinel-2 images.

Projects

21 questions we ask our clients: Starting a successful ML project

By Emilius Richter May 21st, 2021

Read about the 21 relevant questions that should be considered & answered upfront to start a successful machine learning software project.

Use Cases in Government & Public Sector

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