Insight@DCU Deep Learning Workshop #InsightDL2017
Dublin City University Glasnevin Campus, Nursing Building H23 (April 27-28, 2017)
Deep learning technologies are at the core of the current revolution in artificial intelligence for multimedia data analysis. The convergence of big annotated data and affordable GPU hardware has allowed the training of neural networks for data analysis tasks which had been addressed until now with hand-crafted features. Architectures such as convolutional neural networks, recurrent neural networks and Q-nets for reinforcement learning have shaped a brand new scenario in signal processing. This course will cover the basic principles and applications of deep learning to computer vision problems, such as image classification, object detection or text captioning.
Organizers
 |
 |
 |
 |
|---|---|---|---|
| Insight Centre for Data Analytics | Dublin City University (DCU) | UPC Image Processing Group | Universitat Politecnica de Catalunya (UPC) |
Chair
Keynotes
| Speaker | Institution | Slides |
|---|---|---|
| Prof. Alan F. Smeaton | Insight Centre for Data Analytics (DCU) | Machine Learning Overview |
| Dr. Adam Bermingham | Zalando |
Spotlights
| Speaker | Institution | Slides |
|---|---|---|
| Dr. Kevin McGuinness | Insight Centre for Data Analytics (DCU) | Learning where to look |
| Rory Timlin | Accenture | |
| Prof. Xavier Giro-i-Nieto | Techincal University of Catalonia (UPC) | One Perceptron to Rule them All |
| Dr. Alessandra Sala | Nokia Bell Labs | |
| Dr. Deepak Ajwani | Nokia Bell Labs | |
| Dr. Brian MacNamee | Insight Centre for Data Analytics (UCD) | Deep Learning in Deep Space |
Lectures
 |
 |
 |
 |
|---|---|---|---|
| Kevin McGuinness (KM) | Eva Mohedano (EM) | Xavier Giro-i-Nieto (XG) | Amaia Salvador (AS) |
| Topic | Speaker | Slides | Topic | Speaker | Slides |
|---|---|---|---|---|---|
| D1L01 The Perceptron | XG | Slides | D2L01 Unsupervised | KM | Slides |
| D1L02 Deep Neural Networks | EM | Slides | D2L02 Architectures | XG | Slides |
| D1L03 Image Classification | XG | Slides | D2L03 Generative | KM | Slides |
| D1L04 Training | KM | Slides | D2L04 Transfer learning | KM | Slides |
| D1L05 Visualization | AS | Slides | D2L05 Object Detection | AS | Slides |
| D1L06 Optimization | KM | Slides | D2L06 Image retrieval | EM | Slides |
| D2L07 Segmentation | AS | Slides | |||
| D2L08 Recurrent | XG | Slides | |||
| D2L09 Audio & Vision | AS | Slides | |||
| D2L10 Machine translation | XG | Slides | |||
| D2L11 Language & Vision | XG | Slides | |||
| D2L12 Attention Models | AS | Slides | |||
| D2L13 Closing | XG | Slides |
Pictures
Check our photo album on Facebook.
Previous and similar editions from the instructors
- Amaia Salvador and Santiago Pascual, Applied Deep Learning in Keras and TensorFlow. Persontyle 2017.
- Deep Learning for Computer Vision. UPC TelecomBCN 2016.
- Deep Learning for Speech and Language. UPC TelecomBCN 2017.
- Xavier Giro-i-Nieto, “Deep learning for computer vision: Image, Object, Videos Analytics and Beyond”. LaSalle URL. May 2016.
Related courses
- Fei-Fei Li, Andrej Karpathy, Justin Johnson, “CS231n: Convolutional Neural Networks for Visual Recognition”. Stanford University, Spring 2016.
- Sanja Fidler, “Deep Learning in Computer Vision”. University of Toronto, Winter 2016.
- Hugo Larochelle, “Neural Networks”. Université de Sheerbroke.
- Joan Bruna, “Stats212b: Topics on Deep Learning”. Berkeley University. Spring 2016.
- Yann LeCun, “Deep Learning: Nine Lectures at Collège de France”. Collège de France, Spring 2016. [Facebook page]
- Dhruv Batra, “ECE 6504: Deep learning for perception”. Virginia Tech, Fall 2015.
- Vincent Vanhoucke, Arpan Chakraborty, “Deep Learning”. Google 2016.
- German Ros, Joost van de Weijer, Marc Masana, Yaxing Wang, “Hands-on Deep Learning with Matconvnet”. Computer Vision Center (CVC) 2015.
Acknowledgements
This course is co-funded by the Erasmus+ programme from the European Union:
