Paul Bodesheim

Paul Bodesheim

Friedrich-Schiller-Universität Jena

H-index: 16

Europe-Germany

About Paul Bodesheim

Paul Bodesheim, With an exceptional h-index of 16 and a recent h-index of 14 (since 2020), a distinguished researcher at Friedrich-Schiller-Universität Jena, specializes in the field of Computer Vision, Machine Learning, Pattern Recognition.

His recent articles reflect a diverse array of research interests and contributions to the field:

Determining the community composition of herbaceous species from images using convolutional neural networks

Deep learning pipeline for automated visual moth monitoring: insect localization and species classification

Beyond Debiasing: Actively Steering Feature Selection via Loss Regularization

Automated visual monitoring of nocturnal insects with light-based camera traps

Pre-trained models are not enough: active and lifelong learning is important for long-term visual monitoring of mammals in biodiversity researchIndividual identification and …

Towards a multisensor station for automated biodiversity monitoring

Beyond Global Average Pooling: Alternative Feature Aggregations for Weakly Supervised Localization.

Predicting spatiotemporal variability in radial tree growth at the continental scale with machine learning

Paul Bodesheim Information

University

Position

Computer Vision Group Germany

Citations(all)

1512

Citations(since 2020)

1220

Cited By

628

hIndex(all)

16

hIndex(since 2020)

14

i10Index(all)

24

i10Index(since 2020)

19

Email

University Profile Page

Friedrich-Schiller-Universität Jena

Google Scholar

View Google Scholar Profile

Paul Bodesheim Skills & Research Interests

Computer Vision

Machine Learning

Pattern Recognition

Top articles of Paul Bodesheim

Title

Journal

Author(s)

Publication Date

Determining the community composition of herbaceous species from images using convolutional neural networks

Ecological Informatics

Matthias Körschens

Solveig Franziska Bucher

Paul Bodesheim

Josephine Ulrich

Joachim Denzler

...

2024/2/10

Deep learning pipeline for automated visual moth monitoring: insect localization and species classification

arXiv preprint arXiv:2307.15427

Dimitri Korsch

Paul Bodesheim

Joachim Denzler

2023/7/28

Beyond Debiasing: Actively Steering Feature Selection via Loss Regularization

Jan Blunk

Niklas Penzel

Paul Bodesheim

Joachim Denzler

2023/9/19

Automated visual monitoring of nocturnal insects with light-based camera traps

Dimitri Korsch

Paul Bodesheim

Gunnar Brehm

Joachim Denzler

2022

Pre-trained models are not enough: active and lifelong learning is important for long-term visual monitoring of mammals in biodiversity researchIndividual identification and …

Mammalian Biology

Paul Bodesheim

Jan Blunk

Matthias Körschens

Clemens-Alexander Brust

Christoph Käding

...

2022/6

Towards a multisensor station for automated biodiversity monitoring

Basic and Applied Ecology

J Wolfgang Wägele

Paul Bodesheim

Sarah J Bourlat

Joachim Denzler

Michael Diepenbroek

...

2022/3/1

Beyond Global Average Pooling: Alternative Feature Aggregations for Weakly Supervised Localization.

Matthias Körschens

Paul Bodesheim

Joachim Denzler

2022/12

Predicting spatiotemporal variability in radial tree growth at the continental scale with machine learning

Environmental Data Science

Paul Bodesheim

Flurin Babst

David C Frank

Claudia Hartl

Christian S Zang

...

2022/1

Investigating neural network training on a feature level using conditional independence

Niklas Penzel

Christian Reimers

Paul Bodesheim

Joachim Denzler

2022/10/23

Emerging technologies revolutionise insect ecology and monitoring

Roel Van Klink

Tom August

Yves Bas

Paul Bodesheim

Aletta Bonn

...

2022/10/1

Occlusion-Robustness of Convolutional Neural Networks via Inverted Cutout

Matthias Körschens

Paul Bodesheim

Joachim Denzler

2022/8/21

Minimizing the annotation effort for detecting wildlife in camera trap images with active learning

Daphne Auer

Paul Bodesheim

Christian Fiderer

Marco Heurich

Joachim Denzler

2021

End-to-end learning of fisher vector encodings for part features in fine-grained recognition

Dimitri Korsch

Paul Bodesheim

Joachim Denzler

2021/9/28

Conditional dependence tests reveal the usage of ABCD rule features and bias variables in automatic skin lesion classification

Christian Reimers

Niklas Penzel

Paul Bodesheim

Jakob Runge

Joachim Denzler

2021

Automated visual large scale monitoring of faunal biodiversity

Pattern Recognition and Image Analysis

Bernd Radig

Paul Bodesheim

Dimitri Korsch

Joachim Denzler

Timm Haucke

...

2021/7/1

Automatic plant cover estimation with convolutional neural networks

arXiv preprint arXiv:2106.11154

Matthias Körschens

Paul Bodesheim

Christine Römermann

Solveig Franziska Bucher

Mirco Migliavacca

...

2021/6/21

Towards learning an unbiased classifier from biased data via conditional adversarial debiasing

arXiv preprint arXiv:2103.06179

Christian Reimers

Paul Bodesheim

Jakob Runge

Joachim Denzler

2021/3/10

Weakly supervised segmentation pretraining for plant cover prediction

Matthias Körschens

Paul Bodesheim

Christine Römermann

Solveig Franziska Bucher

Mirco Migliavacca

...

2021/9/28

Exploiting web images for moth species classification

Julia Böhlke

Dimitri Korsch

Paul Bodesheim

Joachim Denzler

2021

Conditional adversarial debiasing: Towards learning unbiased classifiers from biased data

Christian Reimers

Paul Bodesheim

Jakob Runge

Joachim Denzler

2021/9/28

See List of Professors in Paul Bodesheim University(Friedrich-Schiller-Universität Jena)