Workshop on Machine Learning Advances for Environmental and Underwater Imaging Data

Workshop on Machine Learning Advances for Environmental and Underwater Imaging Data

8 & 9 June 2023 

National Oceanography Centre Southampton 

The Big Data accumulating from environmental and underwater imagery imposes a series of unique challenges, which need to be tackled by the data scientist community in collaboration with environmental scientists. This workshop is specifically interested in discussing computer vision challenges such as model development, annotation, managing skewed datasets, and poor data quality. We will bring together researchers from both academia and industry across diverse domains of AI, including experts from AI, big data, data transmission, engineering and computer vision, as well as other scientists with an interest in the application of image analysis. We will discuss methods and procedures to cover topics such as: 

  • Cutting-edge AI for the ocean and environmental observation
  • Deep learning and its applications to, e.g., classification, object detection, segmentation and monitoring of marine life
  • Meta-learning, including transfer learning, online learning, and active learning
  • Real-time processing
  • Handling of large data sets with modern techniques such as compression, tiering, and deduplication
  • FAIR data management, image collection, pre-processing, annotation, taxonomically accurate labelling

The workshop will be two days with keynote talks, talks and discussions. A preliminary workshop structure is:

Day 1: Al algorithms and architecture

Day 2: Data handling and management

The workshop is limited to 20 participants. Registration is free, and the workshop will cover refreshments, lunch (both days), and a workshop dinner after the first day. Participants are expected to cover their own expenses for travel, accommodation and breakfast.

Please register your interest to participate:  Click Here 

to download the event flyer please click here

To ensure we have a diverse and relevant audience please note completing this form does not automatically guarantee you a place.  The organising team will be in touch with further information or acceptance to attend  


  This project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 101000858 (TechOceanS). This output reflects only the author’s view and the Research Executive Agency (REA) cannot be held responsible for any use that may be made of the information contained therein

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