activity
20242026
most citedHierarchical Multi-Label Classification with Missing Information for Benthic Habitat Imagery

3 citations · 4 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CV2026

A continental-scale dataset of ground beetles with high-resolution images and validated morphological trait measurements

S M Rayeed, Mridul Khurana, Alyson East +18

Despite the ecological significance of invertebrates, global trait databases remain heavily biased toward vertebrates and plants, limiting comprehensive ecological analyses of high…

cs.LG20251 cited

BarcodeMamba+: Advancing State-Space Models for Fungal Biodiversity Research

Tiancheng Gao, Scott C. Lowe, Brendan Furneaux +2

Accurate taxonomic classification from DNA barcodes is a cornerstone of global biodiversity monitoring, yet fungi present extreme challenges due to sparse labelling and long-tailed…

cs.LG2025

Hyperbolic Multimodal Representation Learning for Biological Taxonomies

ZeMing Gong, Chuanqi Tang, Xiaoliang Huo +6

Taxonomic classification in biodiversity research involves organizing biological specimens into structured hierarchies based on evidence, which can come from multiple modalities su…

cs.CV2025

A multi-modal dataset for insect biodiversity with imagery and DNA at the trap and individual level

Johanna Orsholm, John Quinto, Hannu Autto +26

Insects comprise millions of species, many experiencing severe population declines under environmental and habitat changes. High-throughput approaches are crucial for accelerating…

cs.CV2025

Optimizing Image Capture for Computer Vision-Powered Taxonomic Identification and Trait Recognition of Biodiversity Specimens

Alyson East, Elizabeth G. Campolongo, Luke Meyers +25

1) Biological collections house millions of specimens with digital images increasingly available through open-access platforms. However, most imaging protocols were developed for h…

cs.LG2025

Enhancing DNA Foundation Models to Address Masking Inefficiencies

Monireh Safari, Pablo Millan Arias, Scott C. Lowe +3

Masked language modelling (MLM) as a pretraining objective has been widely adopted in genomic sequence modelling. While pretrained models can successfully serve as encoders for var…