DFKI - Interactive Machine Learning Lab

  • Home
  • Projects
    • Multimodality
    • Machine Learning
    • HCI & Virtual Reality
    • Natural Language Processing
    • Computational Sustainability
    • Lighthouse Project
  • News
  • People
  • Publications
  • Teaching
    • Courses
    • Writing a Thesis
  • Jobs

ELTE and DFKI present two technical papers about deep learning for gaze estimation and hand gestures at KI 2016.

Published by Max Biwersi on September 28, 2016September 28, 2016

KI 2016.

Categories:

Search
Categories
  • Computational Sustainability (7)
  • Machine Learning (13)
  • HCI & Virtual Reality (5)
  • Multimodality (8)
  • Natural Language Processing (13)
  • Lighthouse Project (6)
Article by Year
  • 2026 (5)
  • 2025 (3)
  • 2024 (3)
  • 2023 (8)
  • 2022 (4)
  • 2021 (2)
  • 2020 (3)
  • 2019 (4)
  • 2018 (12)
  • 2017 (3)
  • 2016 (1)
  • 2014 (2)

Related Posts

Computational Sustainability

Interactive Weak Supervision for Transferring Sound Libraries to Passive Acoustic Monitoring

Passive Acoustic Monitoring (PAM) enables continuous and non-invasive biodiversity monitoring, but analysing large acoustic datasets remains difficult because sound event detectors usually require temporally precise annotations. Creating such instance-level labels is expensive and requires expert Read more

Machine Learning

4D reasoning from demonstration data for VLA

Visual-Language-Action (VLA) models are typically trained through imitation learning, which teaches policies to reproduce demonstrated actions but provides limited supervision about the conditions that define task success. We propose a framework that automatically extracts executable Read more

Computational Sustainability

Machine Learning for Passive Acoustic Wildlife Monitoring: Methods for Semi-Automated Population and Species Assessment

Passive acoustic monitoring (PAM) has become a powerful tool for studying wildlife by continuously recording environmental soundscapes. However, analysing large acoustic datasets remains highly time-consuming, as recordings are often annotated manually by domain experts. In Read more

  • AI in Sports
  • DFKI CORE IML
  • Thesis Advisors
Hestia | Developed by ThemeIsle