In this section you will find a variety of resources that I created or I find useful to share with the research community.
Online Course:
Machine learning based image collection, annotation and classification
Machine learning based image collection, annotation and classification
In this free online course you learn about:
This course includes a series of exercises using Python and you can watch the recorded live Q&A sessions run on 25th, 26th and 27th of October 2022.
You can find the course here.
- concepts of data science, machine learning (ML), computer vision, deep learning and Convolutional Neural Networks (CNNs)
- how to pre-process and pre-annotate images to accelerate your ML projects
- how to apply data augmentation techniques
- how to build an image classification model with your own or example data
This course includes a series of exercises using Python and you can watch the recorded live Q&A sessions run on 25th, 26th and 27th of October 2022.
You can find the course here.
Online workshop:
Machine learning tools for species identification and fish size estimation in recreational and small-scale fisheries
2-3 May 2022
Machine learning tools for species identification and fish size estimation in recreational and small-scale fisheries
2-3 May 2022
Day 1:
00:01 - Asta Audzijonyte (Nature Research Center, Lithuania & University of Tasmania, Australia). Introduction, anglers, citizen science and fish size data
10:03 - Daniel Pauly (University of British Columbia, FishBase, Canada). Citizen science data and FishBase
38:47 - Christian Skov (Technical University of Denmark). Fangstjournalen: a citizen science program for anglers
52:19 - Sean Simmons (MyCatch and Angler's Atlas, Canada). Citizen science in fisheries research: angler generated data, validation techniques and opportunities for machine learning
1:09:11 - Lisa Kellogg (Virginia Institute of Marine Science, USA). RecFish: engaging recreational anglers as community scientists: Overview
1:33:00 - Harshil Shah & Divya Shah (DXFactor): RecFish: engaging recreational anglers as community scientists: Technical details
1:53:00 - Nathaniel (Than) Hitt (U.S. Geological Survey): Deep learning for stream fish conservation using images for individual recognition
00:01 - Asta Audzijonyte (Nature Research Center, Lithuania & University of Tasmania, Australia). Introduction, anglers, citizen science and fish size data
10:03 - Daniel Pauly (University of British Columbia, FishBase, Canada). Citizen science data and FishBase
38:47 - Christian Skov (Technical University of Denmark). Fangstjournalen: a citizen science program for anglers
52:19 - Sean Simmons (MyCatch and Angler's Atlas, Canada). Citizen science in fisheries research: angler generated data, validation techniques and opportunities for machine learning
1:09:11 - Lisa Kellogg (Virginia Institute of Marine Science, USA). RecFish: engaging recreational anglers as community scientists: Overview
1:33:00 - Harshil Shah & Divya Shah (DXFactor): RecFish: engaging recreational anglers as community scientists: Technical details
1:53:00 - Nathaniel (Than) Hitt (U.S. Geological Survey): Deep learning for stream fish conservation using images for individual recognition
Day 2:
01:35 - Asta Audzijonyte (Nature Research Center, Lithuania & University of Tasmania, Australia): Introduction and day one recap
09:52 - John Lynham (University of Hawai'i at Mānoa). FishNet: species classification and size regression using AI and a dataset of one million fish
31:33 - Catarina Silva (Nature Research Center, Lithuania): Developing open source tools for automated fish species identification for recreational fisheries
55:31 - Jaume Piera (Spanish National Research Council): Integrating AI tools in Citizen Observatories for potential monitoring of fishes: the case of Cos4Cloud project
01:14:50 - Dadong Wang (Data61, CSIRO, Australia): AI-based video analysis for electronic monitoring of fisheries operation
01:38:10 - Yanyu Chen (University of Tasmania, Australia): Automated sex classification and size estimation for Giant Grabs
01:57:17 - Xabier Lekunberri (AZTI, Basque Research and Technology Alliance): Identification and measurement of tropical tuna species in purse seiners catches using computer vision and deep learning
01:35 - Asta Audzijonyte (Nature Research Center, Lithuania & University of Tasmania, Australia): Introduction and day one recap
09:52 - John Lynham (University of Hawai'i at Mānoa). FishNet: species classification and size regression using AI and a dataset of one million fish
31:33 - Catarina Silva (Nature Research Center, Lithuania): Developing open source tools for automated fish species identification for recreational fisheries
55:31 - Jaume Piera (Spanish National Research Council): Integrating AI tools in Citizen Observatories for potential monitoring of fishes: the case of Cos4Cloud project
01:14:50 - Dadong Wang (Data61, CSIRO, Australia): AI-based video analysis for electronic monitoring of fisheries operation
01:38:10 - Yanyu Chen (University of Tasmania, Australia): Automated sex classification and size estimation for Giant Grabs
01:57:17 - Xabier Lekunberri (AZTI, Basque Research and Technology Alliance): Identification and measurement of tropical tuna species in purse seiners catches using computer vision and deep learning
4th World Small-Scale Fisheries Congress 2022
Parallel session #5.3 - SSF centric data collection and stock status assessment in the digital age
Parallel session #5.3 - SSF centric data collection and stock status assessment in the digital age
This session invites contributions presenting digital methods and tools that can empower small scale fisheries communities to collect data and increase knowledge on the status of populations they are harvesting.
Online workshop:
Can citizen science, smartphone app and social media data be used for recreational fisheries management?
December 15, 2022
Can citizen science, smartphone app and social media data be used for recreational fisheries management?
December 15, 2022