A Step Towards Worldwide Biodiversity Assessment: The BIOSCAN-1M Insect Dataset

1 code implementation • NeurIPS 2023 • Zahra Gharaee, ZeMing Gong, Nicholas Pellegrino, Iuliia Zarubiieva, Joakim Bruslund Haurum, Scott C. Lowe, Jaclyn T. A. McKeown, Chris C. Y. Ho, Joschka McLeod, Yi-Yun C Wei, Jireh Agda, Sujeevan Ratnasingham, Dirk Steinke, Angel X. Chang, Graham W. Taylor, Paul Fieguth

In an effort to catalog insect biodiversity, we propose a new large dataset of hand-labelled insect images, the BIOSCAN-Insect Dataset.

Classification

Machine Learning Challenges of Biological Factors in Insect Image Data

no code implementations • 4 Nov 2022 • Nicholas Pellegrino, Zahra Gharaee, Paul Fieguth

The BIOSCAN project, led by the International Barcode of Life Consortium, seeks to study changes in biodiversity on a global scale.

K-Means for Noise-Insensitive Multi-Dimensional Feature Learning

no code implementations • 15 Feb 2022 • Nicholas Pellegrino, Paul Fieguth, Parsin Haji Reza

Many measurement modalities which perform imaging by probing an object pixel-by-pixel, such as via Photoacoustic Microscopy, produce a multi-dimensional feature (typically a time-domain signal) at each pixel.

Clustering