:: Deep Learning Lab

Monday, 23-Dec-2024, 9:00- 12:00
This workshop introduces deep neural networks and how they being learned. By investigating different deep network models in Python and Matlab programming environments, the audience will learn the programming and implementation of deep neural networks, as well as how to teach them.

Headlines:

Section I:

    - Fundamentals of Neural Network and Deep Learning

    - Convolutional Neural Networks (CNN)

    - Generative Models: GAN and DCGAN

    - Training a DCGAN model in Python

 

Section II:

    - Image classification with CNN

    - Implementation of image classification in Matlab: Brain Tumor Dataset

    - Introduction of Object Detection with CNN

    - Implementation of R-CNN, Fast R-CNN and Faster R-CNN methods in Matlab

 

Section III:

   - Transformers   
   - From RNNs and LSTMs to Transformers

   - Attention and Self-attention mechanisms in Transformers

    - Vision Transformers (ViTs)

   - Structure of ViTs

   - Image classification with ViTs

   - Swin Transformers

   - Image classification with Swin transformers

Workshop Audiance:

This workshop includes students of Engineering and Sciences. Familiarity with mathematical and artificial intelligence concepts can be useful. Also, understanding the basic structures of Python or Matlab programming languages are required.

 

Workshop Organizers:

Dr. E. Mansoori: Assoc. Prof. of CSE&IT Dept. (Coordinator)

Eng. S. Siamak: PhD candidate of Computer Engineering – AI (Interests: Machine Vision, Deep Learning and Deep Reinforcement Learning)

Eng. S. Mehrpou: MSc in Biomedical Engineering – Bioelectric (Interests: Identification of Necessary Proteins using Machine Learning and Deep Learning)

Eng. H. Sadravi: MSc in Biomedical Engineering – Bioelectric (Interests: Biodata Analysis using Deep Learning)