collaborators

6 papers

cs.CV2026

Automatic Image-Level Morphological Trait Annotation for Organismal Images

Vardaan Pahuja, Samuel Stevens, Alyson East +2

Morphological traits are physical characteristics of biological organisms that provide vital clues on how organisms interact with their environment. Yet extracting these traits rem…

cs.CV2026

BeetleFlow: An Integrative Deep Learning Pipeline for Beetle Image Processing

Fangxun Liu, S M Rayeed, Samuel Stevens +21

In entomology and ecology research, biologists often need to collect a large number of insects, among which beetles are the most common species. A common practice for biologists to…

cs.CV2026

BeetleVerse: A Study on Taxonomic Classification of Ground Beetles

S M Rayeed, Alyson East, Samuel Stevens +2

Ground beetles are a highly sensitive and speciose biological indicator, making them vital for monitoring biodiversity. However, they are currently an underutilized resource due to…

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.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.CV2025

Static Segmentation by Tracking: A Label-Efficient Approach for Fine-Grained Specimen Image Segmentation

Zhenyang Feng, Zihe Wang, Jianyang Gu +22

We study image segmentation in the biological domain, particularly trait segmentation from specimen images (e.g., butterfly wing stripes, beetle elytra). This fine-grained task is…