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Nicolas Audebert - Computer Vision & Deep Learning Researcher — 18 websites ranked by shared content topics, category and on-page relevance.

Each result shows its full tech stack, contacts and AI-policy — not just a name · Browse all sites in Artificial Intelligence →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
cyclop.ai ↗	70 match 1 shared topics	Cyclop - Computer Vision & KI-Lösungen	de	artificial-intelligence	robotsllmsaihumans	emailphone	none
instantxr.de ↗	66 match 1 shared topics	eXtended Reality, Computer Vision + AI by Fraunhofer IGD	DE de	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
lern-apparat.de ↗	64 match 1 shared topics	Lernapparat - Machine Learning	DE de	artificial-intelligence	robotsllmsaihumans	emailphone	partial · 1
machine-learning-reply.com ↗	64 match 1 shared topics	Künstliche Intelligenz und Machine Learning \| Machine Learning Reply	de	artificial-intelligence	robotsllmsaihumans	emailphone	none
machine-learningreply.com ↗	64 match 1 shared topics	Künstliche Intelligenz und Machine Learning \| Machine Learning Reply	de	artificial-intelligence	robotsllmsaihumans	emailphone	none
machinelearningreply.com ↗	64 match 1 shared topics	Künstliche Intelligenz und Machine Learning \| Machine Learning Reply	de	artificial-intelligence	robotsllmsaihumans	emailphone	none
machine-learning-reply.de ↗	64 match 1 shared topics	Künstliche Intelligenz und Machine Learning \| Machine Learning Reply	DE de	artificial-intelligence	robotsllmsaihumans	emailphone	none
machinelearningreply.de ↗	64 match 1 shared topics	Künstliche Intelligenz und Machine Learning \| Machine Learning Reply	DE de	artificial-intelligence	robotsllmsaihumans	emailphone	none
machine-learningreply.de ↗	64 match 1 shared topics	Künstliche Intelligenz und Machine Learning \| Machine Learning Reply	DE de	artificial-intelligence	robotsllmsaihumans	emailphone	none
maxpascher.de ↗	64 match 1 shared topics	Hi, I'm Max Pascher - HRI Researcher working with Assistive Robots & XR	DE de	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
ki-deltalearning.de ↗	63 match 1 shared topics	KI Delta Learning: KI Delta Learning	DE de	artificial-intelligence TYPO3	robotsllmsaihumans	emailphone	none
lehmannsuperior.de ↗	63 match 1 shared topics	Florian Lehmann - HCI and AI Researcher Focusing on Mixed-Initiative Interaction with Intelligent Systems	DE de	artificial-intelligence Drupal	robotsllmsaihumans	emailphone	none
2chub.com ↗	63 match 1 shared topics	2CHuB — Center for Computation of Human Behavior	de	artificial-intelligence	robotsllmsaihumans	emailphone	none
learning-machines.de ↗	63 match 1 shared topics	Learning Machines - Learning Machines - Data Science for Sustainability	DE de	artificial-intelligence	robotsllmsaihumans	email phone	none
balthasar.digital ↗	63 match 1 shared topics	BALTHASAR – Nature-Inspired Computation	de	artificial-intelligence WordPress WooCommerce	robotsllmsaihumans	emailphone	none
deepassist.net ↗	62 match 1 shared topics	Customer Service Automation mit deepassist - sicher & vortrainiert	de	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
deepsearch.net ↗	62 match 1 shared topics	Customer Service Automation mit deepassist - sicher & vortrainiert	de	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
7tage.info ↗	62 match 1 shared topics	Übersicht – AI VISIONS	de	artificial-intelligence Joomla	robotsllmsaihumans	emailphone	none

How the match score works

Each match is a 0–100 similarity score — the higher it is, the more two sites resemble one another. It’s computed automatically from our own crawl data (never from what a site says about itself) by combining several independent signals, so a high score means several of them point the same way:

shared topics how many of the same fine‑grained content topics (IAB sub‑categories) both sites cover — the main signal.
same category whether they sit in the same business / industry category.
content & title how closely their titles and page descriptions line up in wording and meaning.

No single signal decides the result — they’re blended together. Treat the score as a way to rank candidates rather than an absolute percentage; the chips on each result show which signals contributed.