activity
20182026
most citedTaxon and trait recognition from digitized herbarium specimens using deep convolutional neural networks

67 citations · 69 across the 5 of their papers we have counts for

collaborators

5 papers

cs.ET2026

An Economic Analysis of DNA-based Data Storage Systems

Alex El-Shaikh, Bernhard Seeger, Thomas Heinis

Deoxyribonucleic acid (DNA) remains stable for millennia without degradation, can store information at densities orders of magnitude higher than current technologies, and is enviro…

cs.DS2023

Exact and Heuristic Approaches to Speeding Up the MSM Time Series Distance Computation

Jana Holznigenkemper, Christian Komusiewicz, Bernhard Seeger

The computation of the distance of two time series is time-consuming for any elastic distance function that accounts for misalignments. Among those functions, DTW is the most promi…

cs.DS2022

On Computing Exact Means of Time Series Using the Move-Split-Merge Metric

Jana Holznigenkemper, Christian Komusiewicz, Bernhard Seeger

Computing an accurate mean of a set of time series is a critical task in applications like nearest-neighbor classification and clustering of time series. While there are many dista…

cs.CV2020★ 2 cited

Detection and Annotation of Plant Organs from Digitized Herbarium Scans using Deep Learning

Sohaib Younis, Marco Schmidt, Claus Weiland +3

As herbarium specimens are increasingly becoming digitized and accessible in online repositories, advanced computer vision techniques are being used to extract information from the…

q-bio.PE2018★ 67 cited

Taxon and trait recognition from digitized herbarium specimens using deep convolutional neural networks

Sohaib Younis, Claus Weiland, Robert Hoehndorf +4

Herbaria worldwide are housing a treasure of 100s of millions of herbarium specimens, which are increasingly being digitized in recent years and thereby made more easily accessible…