Advanced Computer Vision Training in Singapore

Introduction:

Embark on a journey into the dynamic realm of Artificial Intelligence (AI) with our Computer Vision course, designed to help you learn and upskill in this very relevant and useful field. Computer Vision, a crucial facet of AI and Computer Science, empowers computers to gain visual comprehension of the world, leading to transformative applications in face recognition, autonomous cars, image search, optical character recognition, robotics vision, and more. Stay abreast of the latest advancements in Computer Vision through our course, where you’ll delve into cutting-edge techniques like Region-based CNN and YOLO. Gain insights into convolutional neural networks and transfer learning, preparing yourself to address real-world problems in the ever-evolving landscape of AI.

Course Objectives:

  • ConvNET
  • Transfer Learning
  • R-CNN Based Object Detection
  • YOLO Based Object Detection

Duration

7 hours, 1 Day Course

Mode of Delivery

Classroom-based, Instructor-led Training

Course Outlines

  1. Overview of Computer Vision
    1. Computer Vision Tasks
    2. Computer Vision Applications
    3. Setup Google Colab for Keras
  2. ConvNet
    1. What is ConvNET?
    2. ConvNET Architecture
    3. Image Classification for HandWritten Digits
    4. Image Classification for Cats and Dogs Small Dataset
    5. ImageDataGenerator
    6. Fit Generator
    7. Overfitting Issue
    8. Dropout & Data Augmentation
    9. Mini Project – Convnet with User Own Images
  3. Transfer Learning
    1. What is Transfer Learning
    2. Transfer Learning with VGG16 Model
    3. Fine Tuning VGG16 Model for Cats and Dogs Small Dataset
    4. Mini Project – Transfer Learning with User Own Images
  4. R-CNN
    1. R-CNN
    2. Fast R-CNN
    3. Faster R-CNN
    4. Mask R-CNN
    5. Mask R-CNN Demo
  5. YOLO
    1. What is YOLO
    2. YOLO Algorithm
    3. Anchor Boxes
    4. IOU
    5. Non Max Suppression
    6. YOLO v3 Demo