Ariell Friedman

Artificial intelligence and machine learning for Australian marine science: current state and future needs

Ariell Friedman, Kamran Shafi, Scarlett Raine, Christopher Jackett et autres

Australia’s marine estate, one of the world’s largest, supports a blue economy worth more than AU$100 billion annually across fisheries, aquaculture, tourism, offshore energy and maritime operations. Yet Australia’s capacity to monitor and manage these environments is constrained by a widening gap …

Kenya, au (code pays fourni par la source)

Harnessing the power of Squidle + to develop flexible machine learning models

Leonard Günzel, Jacquomo Monk, Chris Jackett, Ariell Friedman et autres

While our ability to capture seafloor imagery has expanded dramatically, extracting information remains a major bottleneck, as annotation is still largely manual, time-consuming, and costly. Machine Learning (ML) classifiers offer a promising solution, but they often lack generalisation as they are typically …

no, au, Kenya, de (code pays fourni par la source)

sajessop/SQAPI: Initial Release

Sarah Ann Jessop, Jacquomo Monk, Ariell Friedman

A package for interacting with SQUIDLE API through r.

au, Kenya (code pays fourni par la source)

sajessop/SQAPI: Initial Release

Sarah Ann Jessop, Jacquomo Monk, Ariell Friedman

A package for interacting with SQUIDLE API through r.

au, Kenya (code pays fourni par la source)

Squidle+: a collaborative platform to manage, discover and annotate marine imagery

Ariell Friedman, Jacquomo Monk, Oscar Pizarro, Dhugal J. Lindsay et autres

The rapid growth of marine imaging has outpaced our ability to efficiently analyse the imagery, creating challenges in data management, collaboration, and standardisation. This paper presents Squidle+, a web-based, collaborative platform for the end-to-end management, delivery, discovery, and annotation of marine imagery. …

Kenya, au, no, jp, us, gb (code pays fourni par la source)

Habibot: A multi-model machine learning approach for rapid classification of temperate rocky reef ecosystems from underwater imagery

Shahrokh Heidari, Arie J. P. Spyksma, Kelsey I. Miller, Ariell Friedman et autres

nz, au (code pays fourni par la source)

Urchinbot: An open-source model for the rapid detection and classification of habitat-modifying sea urchin species

Arie J. P. Spyksma, Kelsey I. Miller, Ariell Friedman, Caitlin Grosvenor et autres

Sea urchin overgrazing can transform vital kelp forest ecosystems into less productive 'urchin barrens'. In southeastern Australia and northeastern New Zealand, overgrazing by three sea urchin species, Evechinus chloroticus, Centrostephanus rodgersii and Heliocidaris erythrogramma, has caused habitat losses across 1000s of kilometres …

nz, it, Kenya, au (code pays fourni par la source)

BenthicNet: A global compilation of seafloor images for deep learning applications

Scott Lowe, Benjamin Misiuk, Isaac Xu, Shakhboz Abdulazizov et autres

Advances in underwater imaging enable collection of extensive seafloor image datasets necessary for monitoring important benthic ecosystems. The ability to collect seafloor imagery has outpaced our capacity to analyze it, hindering mobilization of this crucial environmental information. Machine learning approaches provide opportunities …

ca, br, us, au, no (code pays fourni par la source)

BenthicNet: A global compilation of seafloor images for deep learning applications

Scott Lowe, Benjamin Misiuk, Isaac Xu, Shakhboz Abdulazizov et autres

Advances in underwater imaging enable collection of extensive seafloor image datasets necessary for monitoring important benthic ecosystems. The ability to collect seafloor imagery has outpaced our capacity to analyze it, hindering mobilization of this crucial environmental information. Machine learning approaches provide opportunities …

Report on the Marine Imaging Workshop 2022

Catherine Borremans, Jennifer M. Durden, Timm Schoening, Emma J. Curtis et autres

Imaging is increasingly used to capture information on the marine environment thanks to the improvements in imaging equipment, devices for carrying cameras and data storage in recent years. In that context, biologists, geologists, computer specialists and end-users must gather to discuss the …

Harnessing the Power of Squidle+ to Develop Flexible Machine Learning Models

Leonard Günzel, Jacquomo Monk, Chris Jackett, Ariell Friedman et autres

de (code pays fourni par la source)

SquidJam: A Video Annotation Ecosystem

Mehul Sangekar, Ariell Friedman, Mitsuko Hidaka, Takashi Hosono et autres

Analyses of marine ecosystems requires recording and observing large volumes of images and videos collected from various underwater platforms. In our work, we extensively use multi-camera systems mounted on Remotely Operated Vehicles (ROV) for obtaining videos of marine organisms. Along with these, …

jp (code pays fourni par la source)