Workshops
The first day of the conference, Tuesday 17 December 2024, comprises a range of workshops. Delegates will find these events to be especially valuable where there is a current need to consider the introduction of new AI technologies into their own organisations.
There will be four half-day workshops. Delegates are free to choose any combination of sessions to attend. The programme of workshops is shown below. Note that the first session starts at 11 a.m. to reduce the need for delegates to stay in Cambridge on the previous night.
There is a lunch break from 12.30-13.15 and there are refreshment breaks from 14.45-15.15 and from 16.45-17.00.
Workshops organiser: Professor Adrian Hopgood, University of Portsmouth, UK
Stream 1 Morning (11.00-12.30 and 13.15-14.45 Peterhouse Lecture Theatre)
AI in Education: towards developing international standards
Chair:
Dr Haiming Liu, University of Southampton, UK
This workshop seeks to explore the need for industry standards in AI in education, to understand the requirements and scope for any such standards, identify key stakeholders, and consider the process by which standards might be collaboratively created and agreed. It will work towards the establishment of a network of professionals who can work collaboratively in the development and realisation of such standards.
The workshop will consist of a series of short talks and discussion to:
- establish the current needs and expectations of higher education institutions in relation to AI tools;
- discuss the enterprise opportunities offered by use of AI in education;
- consider how and what kind of industry standards might be created to respond to the needs in the education sector.
Stream 1 Afternoon (15.15-16.45 and 17.00-18.30 Peterhouse Lecture Theatre)
Human-AI collaboration: advancing human, animal, and environmental health
Chair:
Dr Mercedes Arguello Casteleiro, University of Southampton, UK
Human-AI collaboration can bring humans and AI together to gain more valuable insights than either could achieve alone. The workshop goal is to gain an understanding about tasks where human-machine collaboration can facilitate advancements in 'one health', which embraces human, animal, and environmental health. Come along to find out more about the use of AI with human oversight.
Speakers will include:
- Pilar Romero, Animal and Plant Health Agency, UK
- Prof. Kevin Wells, University of Surrey, UK
- Dr Henry Abanda, Oxford Brookes University, UK
- Prof. Juan Carlos Augusto, Middlesex University, UK
- Prof. Adrian Hopgood, University of Portsmouth, UK
Stream 2 Morning (11.00-12.30 and 13.15-14.45 Upper Hall)
Computer Vision Applications of AI - Part 1
Chair: Dr Carla Di Cairano-Gilfedder, BT Labs, UK
Organising Committee: Prof. Jinchang Ren, Prof. Huiyu Zhou, Prof. Lu Liu, Prof. Jan Boehm, Dr James Haworth, and Dr Simon Hadfield
Part 1 of this workshop will comprise scientific presentations around computer vision and remote sensing.
11:00 Multimodal Image Sensing and Fusion for Effective Remote Inspection and Industrial Automation (keynote), Prof. Jinchang Ren, Robert Gordon University, UK
Considering the limitations of single sensors such as colour cameras, synthetic aperture radar (SAR), thermal imaging and even hyperspectral cameras, it is natural to apply and fuse multimodal image sensing for the expanded outreach and enhanced observation, especially in harsh environments e.g. remote sensing. Key techniques and emerging applications of multimodal sensing will be discussed, covering satellite based offshore energy infrastructure detection and measurement, ocean colour remote sensing and Arctic sea ice analysis as well as lab-based or production-line driven industrial automation.
11:50 Title TBC, Dr James Haworth, University College London (UCL)
12:30 Lunch
13:15 Artificial intelligence and its applications in remote sensing (keynote), Prof. Huiyu Zhou, University of Leicester, UK
Recently, deep learning technologies have been widely used for remote sensing applications. In this talk, I will first introduce the characteristics and classification of remote sensing images. Then, I discuss the current challenges in remote sensing and our proposed solutions. Finally, I predict the future work in remote sensing in addition to the summary of the talk.
14:05 Developing Robust Foundation Models for Reliable Remote Sensing Image Understanding, Dr Tianjin Huang, University of Exeter, UK.
Remote sensing images are highly susceptible to various factors, such as weather conditions, sensor variability, and imaging angles, which can introduce significant noise and variability in the acquired data. Therefore, developing robust foundation models for remote sensing is crucial to enhance the models' ability to adapt to noise and data variability. Such models would ensure consistent and reliable results under diverse conditions, making them academically and practically valuable. In the era of foundation models, this presentation aims to discuss the key challenges and solutions for improving the resilience of these foundation models in handling noisy and diverse remote sensing data.
14:45 End
Stream 2 Afternoon (15.15-16.45 and 17.00-18.30 Upper Hall)
Computer Vision Applications of AI - Part 2
Chair: Dr Carla Di Cairano-Gilfedder, BT Labs, UK
Organising Committee: Prof. Jan Boehm, Dr James Haworth, and Dr Simon Hadfield
Part 2 of this workshop will comprise two tutorial sessions.
15:15 Transforming Raw Earth-Observation Data into AI-Ready Datasets using SentinelHub - Dr Simon Hadfield, University of Surrey, UK
Earth Observation (EO) data is captured daily from a variety of orbiting payloads. It is a prime example of a data-intensive industry where AI has tremendous potential but faces significant data access and labelling challenges. This tutorial will explore how to overcome these challenges using SentinelHub which provides on-request access to a wide range of labelled satellite imagery. The focus will be on leveraging SentinelHub’s API to search ML-ready data captures and how to integrate classical computer vision techniques with the platform's data to autonomously label other specialist/non-public data collections.
16:45 Tea break
17:00 Understanding Urban Scenes with AI - Prof. Jan Boehm and Dr James Haworth, University College London (UCL), UK
18:30 End
|
|
AI-2024 Forty-fourth SGAI International Conference on Artificial Intelligence
CAMBRIDGE, ENGLAND 17-19 DECEMBER 2024
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
paper submission and info for authors |
|
|
|
|
