7 papers
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…
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…
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…
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…
BioBench: A Blueprint to Move Beyond ImageNet for Scientific ML Benchmarks
Samuel Stevens
ImageNet-1K linear-probe transfer accuracy remains the default proxy for visual representation quality, yet it no longer predicts performance on scientific imagery. Across 46 moder…
Mind the (Data) Gap: Evaluating Vision Systems in Small Data Applications
Samuel Stevens, S M Rayeed, Jenna Kline
The practical application of AI tools for specific computer vision tasks relies on the "small-data regime" of hundreds to thousands of labeled samples. This small-data regime is vi…