- 38 (Registered)
When : 10th to 11th July 2020
Course Desciption
Deep learning added a huge boost to the already rapidly developing field of computer vision. With deep learning, a lot of new applications of computer vision techniques have been introduced and are now becoming parts of our everyday lives. These include face recognition and indexing, photo stylization or machine vision in self-driving cars.
The goal of this course is to introduce students to computer vision, starting from basics and then turning to more modern deep learning models. We will cover both image and video recognition, including image classification and annotation, object recognition and image search, various object detection techniques, motion estimation, object tracking in video, human action recognition, and finally image stylization, editing and new image generation. In course project, students will learn how to build face recognition and manipulation system to understand the internal mechanics of this technology, probably the most renown and oftenly demonstrated in movies and TV-shows example of computer vision and AI.
Course Content
-
Day 01 - Module-1 Introduction to image processing and computer vision 0/7
-
Lecture1.1
-
Lecture1.2
-
Lecture1.3
-
Lecture1.4
-
Lecture1.5
-
Lecture1.6
-
Lecture1.7
-
-
Module-2 Convolutional features for visual recognition 0/11
-
Lecture2.1
-
Lecture2.2
-
Lecture2.3
-
Lecture2.4
-
Lecture2.5
-
Lecture2.6
-
Lecture2.7
-
Lecture2.8
-
Lecture2.9
-
Lecture2.10
-
Lecture2.11
-
-
Day 02 - Module-1 Object detection 0/12
-
Lecture3.1
-
Lecture3.2
-
Lecture3.3
-
Lecture3.4
-
Lecture3.5
-
Lecture3.6
-
Lecture3.7
-
Lecture3.8
-
Lecture3.9
-
Lecture3.10
-
Lecture3.11
-
Lecture3.12
-
-
Module-2 Object tracking and action recognition 0/11
-
Lecture4.1
-
Lecture4.2
-
Lecture4.3
-
Lecture4.4
-
Lecture4.5
-
Lecture4.6
-
Lecture4.7
-
Lecture4.8
-
Lecture4.9
-
Lecture4.10
-
Lecture4.11
-
-
Module-3 Image segmentation and synthesis 0/7
-
Lecture5.1
-
Lecture5.2
-
Lecture5.3
-
Lecture5.4
-
Lecture5.5
-
Lecture5.6
-
Lecture5.7
-
Instructor
Arun Panayappan is the Founder of Techcovery Solutions which has been in the training and consulting business for three years now. Arun Panayappan was the Vice President, Platform Engineering at www.goibibo.com which is India’s largest online travel agent. He has over 23 years of IT experience including 4 years of overseas experience.Techcovery has trained over 1000 participants in Data science and mentored 4 start ups during its existence. He has worked as a consulting CTO for companies like cogknit semantics, FirstIPO and Trip38. He is frequently consulted for data science architecture and strategy by corporations across the industry. In his role at Amazon, his technical decision-making skills enabled Kindle Topaz Operations Console to go global and scale seamlessly to meet seasonal load. He drove initiatives to hire and develop the best for the Category Expansions team that doubled in size during his leadership tenure while launching 70 new stores for www.amazon.com every year. He built highly scalable web crawling systems to monitor price changes at competitor sites for millions of products sold by Amazon. This system used statistical machine learning and modeled crawl frequencies using poison distribution. His team built the on-boarding experience of vendor platform(https://vendorexpress.amazon.com) to onboard and manage small and medium size vendors to increase selection and buying options. Prior to joining Amazon, he worked for Kuliza (www.kuliza.com), young start up by ex-Amazon employees, and had served the Research team at Accenture Technology Labs., India. He is an innovative and a tech-savvy leader. He sets a high bar for himself and his team on software design, quality and processes. He has a pleasing personality and excellent communication skills.