Advanced Image Recognition with Mask R-CNN

Aniket Rangrej, Data Scientist II, FogHorn Systems
Ravi Ilango, Sr Data Scientist, FogHorn Systems

Agenda
6:30 Doors Open, Food & Networking
7:00 Presentation
*** Please arrive by 7:00 PM due to Security ***
8:30 wrap up

Event Details
We will cover the progression of deep learning technologies leading up to Mask R-CNN: Convolutional Neural Networks (CNN), Fast R-CNN, Faster R-CNN and Mask R-CNN. Originally, images were labeled with one object name per image, such as “cat”. Then, bounding box rectangles were used to label one or more objects within an image. Now, with masking, the irregular outlines of the object are identified in the image, including overlapping instances of the same object. We will also provide a software demo.

See also:
https://arxiv.org/pdf/1703.06870.pdf (Mask R-CNN paper from Facebook AI Research, 2018)

Speakers Bio
Aniket is a Data Scientist at FogHorn Systems, solving industrial use cases in computer vision and machine learning. Aniket has done M-Tech in Computer Science and Engineering from Indian Institute of Technology Madras (IIT-M) and has over 7 years of experience in data science, big data and application development. Before joining FogHorn systems, he has worked in Yahoo R&D, Reliance and Hilabs. Aniket has good exposure in text mining and has conference and journal publications in World Wide Web conference and BMC Bioinformatics. https://www.linkedin.com/in/aniket-rangrej-0a661b20/
(Aniket will be presenting from Pune)

https://www.linkedin.com/in/raviilango/
Ravi is a Sr Data Scientist at FogHorn Systems, working on a variety of revenue-generating projects for clients involving machine learning and deep learning. He has prior experience as a Sr Data Scientist at Apple for 10 years, and a Sr Program Manager at Applied Materials, among other things. He has an MBA from Santa Clara University, Aeronautics and Production Engineering degree from IIT, Madras, and a number of recent Stanford University ML and AI certificates.
(Ravi will be presenting in person, and giving a demo).