Workshop

Full Day Workshop on Deep Learning for Computer Vision

Deep learning has added a boost to the rapidly developing field of computer vision. Computer Vision is the art of distilling actionable information from images and deep learning boosts it by providing powerful tools to do so. With deep learning, a lot of new applications of computer vision techniques have been introduced and are now becoming parts of our everyday lives. To break into this one of the fastest-growing career fields, one needs to have the knowledge of both deep learning and computer vision. This workshop aims at familiarizing the participants with the key concepts of Deep Learning techniques applied in the field of Computer Vision.

Date

13th Aug at Computer Vision DevCon 2020

FORMAT

Full day virtual workshop from 10am to 5pm


Curriculum

The workshop aims at familiarizing the participants with the key concepts of Deep Learning techniques applied in the field of Computer Vision.

  • Introduction to computer vision
    • Introduction and applications
    • Reading and processing images using Python
    • Basic image transformations using Python
    • Image augmentation
  • Deep learning
    • Introduction
    • Convolutional Neural Networks (CNNs)
    • Defining CNNs using Keras
    • Training CNN for image classification
    • Multiclass classification and image recognition
  • Transfer Learning
    • Introduction
    • Transfer learning frameworks – VGG, ResNet, Inception, Mobilenet, Efficientnet
    • Using pre-trained models for transfer learning
    • Image classification through transfer learning models
  • Object Detection
    • Introduction
    • Object detection in scene images
    • Real-time object detection using ImageAI
  • Advanced Computer Vision
    • Neural Style Transfer
    • Generative Adversarial Networks

Prerequisites

  • Knowledge of Python programming language and the basic idea of TensorFlow and GPU.
  • Basic understanding of artificial neural networks and Keras library.
  • Understanding of tensors and clear concepts of matrices and vectors.
  • Good internet connection to load the datasets during program execution.
  • Familiarity with Google Colab

Required Tools

  • Google Colab
  • If working in Jupyter notebook or Spyder editor of Anaconda:-
    • NumPy, Pandas, TensorFlow, Keras, CV2 libraries pre-installed
  • High-speed Internet connectivity

Learning Outcomes

Understand the concept of deep learning and its applications in computer vision.
Knowledge of Deep Convolutional Neural Networks.
Understand the transfer learning frameworks and their real-life applications.
Hands-on knowledge of the state of the art transfer learning models including VGG, ResNet, Inception etc.
Thorough knowledge of Generative Adversarial Networks (GANs) with their practical implementation.
Understand the Neural Style Transfer.
Hands-on knowledge of object detection in images.

  • Early Bird Pass

    Available till 10th July
  • Access to all tracks & workshops
  • Access the recorded sessions later
  • Certificate of attendance provided
  • Access to online networking with attendees & speakers
  • Group discount available
  • $25
  • Regular Pass

    AVAILABLE FROM 10TH JULY TO 31st July
  • Access to all tracks & workshops
  • Access the recorded sessions later
  • Certificate of attendance provided
  • Access to online networking with attendees & speakers
  • Group discount available
  • $50