Christoph Käding - Concepedia

Author

Christoph Käding

Friedrich Schiller University Jena ORCID

Also Known As

Christoph Kading, Christoph Käding, Käding, Christoph

Publications

545

Citations

H-Index

Concepts

All Affiliations

Friedrich Schiller University Jena

About

Christoph Käding is an author at Friedrich Schiller University Jena specializing in engineering, data science, and computer science.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	7	7	286
2	Computer Science	7	7	286
3	Data Science	7	7	286
4	Medicine	1	1	19
5	Cognitive Science	1	1	38

Christoph Käding

Publications

368

Citations

H-Index

Page 1

	Year	Citations
Towards Automated Visual Monitoring of Individual Gorillas in the Wild Clemens-Alexander Brust, Tilo Burghardt, Milou Groenenberg, PrimatologyEngineeringMachine LearningBiometricsImage Sequence Analysis	2017	79
Active Learning for Deep Object Detection Clemens-Alexander Brust, Christoph Käding, Joachim Denzler Artificial IntelligenceMultiple Instance LearningEngineeringMachine LearningDeep Models	2019	62
Active learning and discovery of object categories in the presence of unnameable instances Christoph Käding, Alexander Freytag, Erik Rodner,	2015	57
Active Learning for Deep Object Detection Clemens-Alexander Brust, Christoph Käding, Joachim Denzler Artificial IntelligenceMultiple Instance LearningEngineeringMachine LearningDeep Models	2019	45
Active and Continuous Exploration with Deep Neural Networks and Expected Model Output Changes Christoph Käding, Erik Rodner, Alexander Freytag, arXiv (Cornell University) Artificial IntelligenceFew-shot LearningMultiple Instance LearningEngineeringMachine Learning	2016	38
Active and Continuous Exploration with Deep Neural Networks and Expected\n Model Output Changes Christoph Käding, Erik Rodner, Alexander Freytag, arXiv (Cornell University)	2016	25
Active Learning for Regression Tasks with Expected Model Output Changes. Christoph Käding, Erik Rodner, Alexander Freytag, British Machine Vision Conference Artificial IntelligenceEngineeringMachine LearningData ScienceActive Inference	2018	23
Active and Incremental Learning with Weak Supervision Clemens-Alexander Brust, Christoph Käding, Joachim Denzler KI - Künstliche Intelligenz Artificial IntelligenceIncremental LearningMultiple Instance LearningEngineeringMachine Learning	2020	20
Pre-trained models are not enough: active and lifelong learning is important for long-term visual monitoring of mammals in biodiversity research—Individual identification and attribute prediction with image features from deep neural networks and decoupled decision models applied to elephants and great apes Paul Bodesheim, Jan Blunk, Matthias Körschens, Mammalian Biology Convolutional Neural NetworkMultiple Instance LearningEngineeringMachine LearningAbstract Animal Re-identification	2022	19

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