Skip to main content

Advanced Search

Projected result for your current search: 0

Search Operators:

You can use operators in your search query to narrow down your results even more. Click on the search operator to see an explanation of how it works.
Finds documents with exactly this word group, in exactly this word order and spelling (e.g. "employer branding").
Finds documents with both search terms (e.g. sales AND bonus).
Finds documents with one or the other search term (e.g. porsche OR volkswagen).
Finds documents with all search terms. Blank space is understood as AND (e.g. man robot production).
Finds documents with no appearance of the word behind NOT (e.g. ford NOT "harrison ford").
Finds documents where the search term is mentioned at least "n" times."n" may be any number (e.g. COUNT(gear)>8).
Finds documents with both search terms in any word order, permitting "n" words as a maximum distance between them. Best choose between 15 and 30 (e.g. NEAR(recruit, professionals, 20)).
Finds documents with the search term in word versions or composites. The asterisk * marks whether you wish them BEFORE, BEHIND, or BEFORE and BEHIND the search term (e.g. lightweight*, *lightweight, *lightweight*).
Finds documents with the search term in different spellings. "?" allows only one character (e.g. organi?ation).
Special characters are understood as AND (e.g. Miller Bros. & Sons).

Semantic Search

powered by (Link opens in a new window)
loading …
Log in
Top
KI - Künstliche Intelligenz

Interview: Cyrill Stachniss’ View on AI in Agriculture

  • 17-04-2024
  • Interview
Published in:
Authors
Joachim Hertzberg
Benjamin Kisliuk
Jan Christoph Krause
Cyrill Stachniss
Published in
KI - Künstliche Intelligenz | Issue 2-4/2023

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Excerpt

Cyrill Stachniss, a full professor at the University of Bonn, shares his views on the integration of AI in agriculture, particularly through the PhenoRob cluster. The interview delves into the interdisciplinary collaboration between AI and agricultural experts, highlighting the challenges and successes of applying AI technologies in farming. Stachniss discusses the specific applications of AI in weeding and phenotyping, and the potential for sustainable agriculture. He also touches on the future of AI in agriculture, including the shift towards more hybrid AI models and the importance of data privacy and ownership. The article provides a comprehensive overview of the current state and future directions of AI in agriculture, making it a valuable read for professionals and specialists in the field.
AI Generated

This summary of the content was generated with the help of AI.

Please log in to get access to your license.

Log in Register for free

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Business + Economics & Engineering + Technology"

Online-Abonnement

Springer Professional "Business + Economics & Engineering + Technology" gives you access to:

  • more than 102.000 books
  • more than 537 journals

from the following subject areas:

  • Automotive
  • Construction + Real Estate
  • Business IT + Informatics
  • Electrical Engineering + Electronics
  • Energy + Sustainability
  • Finance + Banking
  • Management + Leadership
  • Marketing + Sales
  • Mechanical Engineering + Materials
  • Insurance + Risk


Secure your knowledge advantage now!

inform now

KI - Künstliche Intelligenz

The Scientific journal "KI – Künstliche Intelligenz" is the official journal of the division for artificial intelligence within the "Gesellschaft für Informatik e.V." (GI) – the German Informatics Society - with constributions from troughout the field of artificial intelligence.

inform now

Springer Professional "Business + Economics"

Online-Abonnement

Springer Professional "Business + Economics" gives you access to:

  • more than 67.000 books
  • more than 340 journals

from the following specialised fileds:

  • Construction + Real Estate
  • Business IT + Informatics
  • Finance + Banking
  • Management + Leadership
  • Marketing + Sales
  • Insurance + Risk



Secure your knowledge advantage now!

inform now
Show more products
previous article AI in Current and Future Agriculture: An Introductory Overview
next article Data Augmentation for Mask-Based Leaf Segmentation of UAV-Images as a Basis to Extract Leaf-Based Phenotyping Parameters
Title
Interview: Cyrill Stachniss’ View on AI in Agriculture
Authors
Joachim Hertzberg
Benjamin Kisliuk
Jan Christoph Krause
Cyrill Stachniss
Publication date
17-04-2024
Publisher
Springer Berlin Heidelberg
Published in
KI - Künstliche Intelligenz / Issue 2-4/2023
Print ISSN: 0933-1875
Electronic ISSN: 1610-1987
DOI
https://doi.org/10.1007/s13218-023-00831-8
This content is only visible if you are logged in and have the appropriate permissions.

Other articles of this Issue 2-4/2023

AI in Current and Future Agriculture: An Introductory Overview

  • Open Access
  • Technical Contribution

How to design a value-based Chatbot for the manufacturing industry: An empirical study of an internal assistance for employees

  • Open Access
  • Project Reports

Zauberzeug Learning Loop

  • AI Transfer

Grassland Yield Estimation Using Transfer Learning from Remote Sensing Data

  • AI Transfer

Visual Module Exploration: A Live-User Evaluation

  • Technical Contribution

Increasing the Value of XAI for Users: A Psychological Perspective

  • Open Access
  • Technical Contribution

Premium Partner

    Image Credits
    Neuer Inhalt/© ITandMEDIA, Nagarro GmbH/© Nagarro GmbH, AvePoint Deutschland GmbH/© AvePoint Deutschland GmbH, AFB Gemeinnützige GmbH/© AFB Gemeinnützige GmbH, USU GmbH/© USU GmbH, Ferrari electronic AG/© Ferrari electronic AG