What is deep learning and what is its role in the computer visionrevolution?
During this conference, we will introduce the necessary ingredients to develop computer vision models based on deep learning, identifying the key points to achieve models with the best possible performance.
- All this from a model development perspective for real-world computer vision applications: industry, health, agriculture, etc.
- We will also present real use cases of computer vision in which deep learning has been key to the development of an effective solution.
- We will discuss the future challenges of this technology (applications with low data availability or annotations, reliable models, real time, model drift, etc.).
Target Audience
- Anyone with an interest in how the technology that is enabling the current artificial intelligence revolution and computer vision works.
- Those who want to exploit the data they have in their company to improve their processes but do not know how.
Programme
- What is computer vision and why is deep learning important for its development?
- What is deep learningbased on? Why now?
- Ingredients for the development of deep learning-based computer vision models and keys to success
- Typical workflow in the development of deep learningmodels
- Success Stories
- Future challenges
Speaker
- Laura Gómez, graduate in Telecommunications Technology Engineering (2017) from the Bilbao School of Engineering (UPV/EHU). She was awarded the Extraordinary End of Degree and Master's Degree in Telecommunications Engineering (2019) by the same university. She did her Final Degree Project within the BioRes research group at the Bilbao School of Engineering in the field of biomedical signal processing. In the last year of her Master's degree, she joined TECNALIA’s Computer Vision research group, where she completed her Master's thesis. Since then, she has been working as a researcher.
- During this time, she has worked on developing deep learning models for computer vision. She has been actively involved in the development of solutions for multinational companies, such as BASF under private research contracts. She is also currently working on her PhD thesis on semi-supervised methods for deep learning models in the field of imaging. She has four European and international patents.