Description:

Semantic Segmentation of an image is to assign each pixel in the input image a semantic class in order to get a pixel-wise dense classification. While semantic segmentation/scene parsing has been a part of the computer vision community since late 2007, but much like other areas in computer vision, a major breakthrough came when fully convolutional neural networks were first used by 2014 Long et. al. to perform end-to-end segmentation of natural images. An introduction to classification network and how it can be seen/converted to a segmentation network i.e a fully-integrated segmentation workflow, allowing you to create image segmentation and analyze the output of a segmentation network.

I will walk through my experience and the problems faced when trying to make a state of the art industry-grade implementation. Some of the points I will try to cover. <ul> <li>An intuitive introduction and visualization of the Convolution Neural Netowrk (the lifeline of Computer Vision).</li> <li>An explanation and small demo of Classification Network using PyTorch.</li> <li>Covering the bridge of Classification and Segmentation.</li> <li>A small demo of fully-integrated segmentation workflow, allowing you to create visualize and understand segmentation datasets and visualize the output of a segmentation network.</li> <li>Importance of data and problems faced by me working on Industry projects.</li> <li>Wrap up and project discussion.</li> </ul>

Prerequisites:

Zeal to learn new things would be enough but basic knowledge of Python would be good to go but the following are always encouraged: - Basic Knowledge of algebra and Python Libraries such as Numpy - Basic knowledge of working with Neural Network (not a strict requirement)

Content URLs:

<a href="https://vibrantabhi19@github.io"> Personal Blog</a>

<a href="https://medium.com/@matelabs_ai/how-these-researchers-tried-something-unconventional-to-came-out-with-a-smaller-yet-better-image-544327f30e72"> A naive Medium Blog sharing light on classification network</a>

I will be putting the presentation links soon.

Speaker Info:

I am presently working as Deep Learning Scientist at Predible Health, here, we have build state of the art segmentation network for liver, tumour and vessel segmentations. I have spoken previously at Shri Mata Vaishno Devi University at their SFD celebrations and I am also speaking at PyCon Hyderabad and at MuPy (Manipal Institute of Technology's annual Python Conference) later this year. I have been a constant contributor in the open source world and have been attending PyCon and other conferences every year. An athlete, a Real Madrid F.C follower and a part time stand-up comedian (good enough to make you laugh). See you at PyCon.

Speaker Links:

<a href="https://vibrantabhi19@github.io"> Personal Blog</a></br>

<a href="https://github.com/vibrantabhi19"> Github Link</a>

<a href="https://www.linkedin.com/in/abhishek-kumar-74299887/"> LinkedIn Profile</a>

<a href="https://twitter.com/abhi_kumar07"> Twitter handle</a>

<a href="https://www.facebook.com/vibrantabhi"> Facebook </a>

Feel free to drop a review or message regarding the talk or ML/DL in general.