Tim W. Nattkemper

About Tim W. Nattkemper

Tim W. Nattkemper, With an exceptional h-index of 38 and a recent h-index of 22 (since 2020), a distinguished researcher at Universität Bielefeld, specializes in the field of Bioinformatics, Bioimage Informatics, Underwater Image Analysis, Visualization, Data Mining.

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

Deep learning–assisted biodiversity assessment in deep-sea benthic megafauna communities: a case study in the context of polymetallic nodule mining

Report on the Marine Imaging Workshop 2022

The exploration and annotation of large amounts of visual inspection data for protective coating systems on stationary marine steel structures

Improving deep learning-based segmentation of diatoms in gigapixel-sized virtual slides by object-based tile positioning and object integrity constraint

An online platform for the management of digital visual data for the condition monitoring of protective coatings on marine steel structures

Künstliche Intelligenz vs. Maritime Korrosion-Where do we go?

Accelerating ocean species discovery and laying the foundations for the future of marine biodiversity research and monitoring

A data science approach for multi-sensor marine observatory data monitoring cold water corals (Paragorgia arborea) in two campaigns

Tim W. Nattkemper Information

University

Position

Professor of Computer Science

Citations(all)

4711

Citations(since 2020)

1796

Cited By

3516

hIndex(all)

38

hIndex(since 2020)

22

i10Index(all)

104

i10Index(since 2020)

48

Email

University Profile Page

Google Scholar

Tim W. Nattkemper Skills & Research Interests

Bioinformatics

Bioimage Informatics

Underwater Image Analysis

Visualization

Data Mining

Top articles of Tim W. Nattkemper

Deep learning–assisted biodiversity assessment in deep-sea benthic megafauna communities: a case study in the context of polymetallic nodule mining

Frontiers in Marine Science

2024/4/17

The exploration and annotation of large amounts of visual inspection data for protective coating systems on stationary marine steel structures

Ocean Engineering

2023/6/15

Improving deep learning-based segmentation of diatoms in gigapixel-sized virtual slides by object-based tile positioning and object integrity constraint

Plos one

2023/2/24

An online platform for the management of digital visual data for the condition monitoring of protective coatings on marine steel structures

Stahlbau

2023/2/1

Künstliche Intelligenz vs. Maritime Korrosion-Where do we go?

2023/12/7

Accelerating ocean species discovery and laying the foundations for the future of marine biodiversity research and monitoring

Frontiers in Marine Science

2023/9/27

A data science approach for multi-sensor marine observatory data monitoring cold water corals (Paragorgia arborea) in two campaigns

PloS one

2023/7/19

A digital light microscopic method for diatom surveys using embedded acid-cleaned samples

Water

2022/10/21

First insights on Vazella pourtalesii assemblage dynamics

2022/10/20

Exploring time series of hyperspectral images for cold water coral stress response analysis

Plos one

2022/8/8

The impact of data augmentations on deep learning-based marine object classification in benthic image transects

Sensors

2022/7/19

Making marine image data FAIR

Scientific data

2022/7/15

MetHoS: a platform for large-scale processing, storage and analysis of metabolomics data

BMC bioinformatics

2022/7/8

A Digital Twin concept for the prescriptive maintenance of protective coating systems on wind turbine structures

Wind Engineering

2022/6

A data-based model for condition monitoring and maintenance planning for protective coating systems for wind tower structures

Renewable energy

2022/3/1

Automated analysis of haematopoietic cells in bone marrow microscopy images

2022

Digitalisierung und Verarbeitung von Sensordaten für die Zustandsbewertung von Oberflächenschutzsystemen stählerner Türme von Onshore‐Windenergieanlagen

Stahlbau

2021/7

The quest for seafloor macrolitter: a critical review of background knowledge, current methods and future prospects

2021/1/19

Fast Visual Exploration of Mass Spectrometry Images with Interactive Dynamic Spectral Similarity Pseudocoloring

Scientific Reports

2021/2/25

See List of Professors in Tim W. Nattkemper University(Universität Bielefeld)

Co-Authors

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