CodeEmporium
In this video, we will take a look at new type of neural network architecture called “Masked Region based Convolution Neural Networks”, Masked R-CNN for short. And in the process, highlight some key sub problems in computer vision.
Please SUBSCRIBE to the channel for more content on Machine Learning, Deep Learning, Data Science, and Artificial Intelligence. Hoping to build a community of AI geeks. You’ll fit right in!
REFERENCES
Main paper: https://arxiv.org/pdf/1703.06870v3.pdf
Code: https://github.com/facebookresearch/Detectron
Convolution Neural networks: https://www.youtube.com/watch?v=m8pOnJxOcqY
Semantic segmentation in deep learning: http://blog.qure.ai/notes/semantic-segmentation-deep-learning-review
Top papers: http://www.arxiv-sanity.com/top?timefilter=alltime&vfilter=all
Recurrent Instance Segmentation: http://www.robots.ox.ac.uk/~tvg/publications/2016/RIS7.pdf
Mask R-CNN Presentation by the Author: https://www.youtube.com/watch?v=g7z4mkfRjI4
Mark Jay’s Video: https://www.youtube.com/watch?v=2TikTv6PWDw
COCO dataset: http://cocodataset.org/#home
Fully Convolutional Networks: https://people.eecs.berkeley.edu/~jonlong/long_shelhamer_fcn.pdf
Faster R-CNN explained: https://medium.com/@smallfishbigsea/faster-r-cnn-explained-864d4fb7e3f8
Notes/summary of Masked R-CNN: http://www.shortscience.org/paper?bibtexKey=journals/corr/HeGDG17#aleju
Music at : https://www.bensound.com/royalty-free-music/track/tenderness
Source
Great video, keep rocking.
Great Explanation, will follow your videos! Thanks for the share
how to prepare own dataset for this I dont want to use cocodataset
thank you
Thanks!!!
nice explanation. subbed
This is great! Please keep on making stuff like this xD.
Gr8 work dude.Subscribed
At 6:41 what is "analog is 2 a 1 versus rest approach"? Thank you very much.
I want to classify body movements. What are your ideas?
Can I please get the ppt?
Amazing video
Excellent video!
Nice work man!!!!
At 3:48, how exactly does max pool rotational invariance?? I understand translational invariance but a rotation would make different features activated
Great video and explanation. I used the model to detect lanes in roads using the Culanes Dataset with very good results. The project is in Github by the name RMASK_Lane_Detection
Just found another great tutorial on AI
Great video
Thank you for the explanation!! Can you share me your slides?
Good summary and ROI ALIGN description.
Thanks! m/
Subbed this is a really really well made easy to understand video. Hope to see more from you in the future!
very nice explanation. Thanks
At first thank you very much for this video. Your videos quality are very good. I have started to watch your videos. Can you
Using Mask RCNN we can detect human class, from that human class can we detect human face ? Then which algorithm will i use to detect face ? Can you please give me some suggestions. And is it possible to use same dataset for human detection along with face detection ??
Nice explanation especially on the ROI align part! I understood based on your explanation!!! Thanks!
Awesome. Thanks!!
Great explanation, thanks a lot! Can I ask what you mean when you say "when computing the mask, a loss of KM squared is incurred" at 6:44?
Do u know where I can find a code for it
Very detailed video. Thank you very much.
Nice, You made it look easy!
Thank you great work! Is there an easy (beginner friendly) explanation how ROI align works?
preciate you stay blessed
If i want to use pretrained R-CNN for my own dataset to segment ( delineate) background from foerground , do i need to annotated or label my data ? The data i am using if person image ..
Nhà thông minh của trí tuệ nhân tạo????
Thu thập thói quen hành vi người dùng hay đi qua chung một tuyến đường của trí tuệ nhân tạo
Đánh dấu địa điểm thường xuyên đến
Tự động đánh dấu phân biệt sắp xếp vào những người và điểm thường lui tới vào kho
Thank you for taking the time and efforts to make this video.
Side note: the creepy whispered "subscribe" at the end of the video has more of a repulsive effect and doesn't really make me want to subscribe (more like making me want to close the video as fast as possible). The positive energy given during the video would probably work a lot better if it were used to ask for subscription too.
Please make a video related to visual question answering