Mask R-CNN for Object Detection in Keras
Use Keras to build the Mask R-CNN model for object detection and segmentation
https://youtu.be/c1xCaw1tcQQ
Use Keras to build the Mask R-CNN model for object detection and segmentation
https://youtu.be/c1xCaw1tcQQ
YouTube
Mask R-CNN for Object Detection
This video covers how to get set up and running with Mask R-CNN for object detection with Keras.
You can find the full code and run it on a free GPU here:
https://ml-showcase.paperspace.com/projects/object-detection-with-mask-r-cnn
Presented by Machine…
You can find the full code and run it on a free GPU here:
https://ml-showcase.paperspace.com/projects/object-detection-with-mask-r-cnn
Presented by Machine…
Reinforcement Learning Course at ASU, Spring, 2021
Dimitri Bertsekas: https://www.youtube.com/playlist?list=PLmH30BG15SIp79JRJ-MVF12uvB1qPtPzn
#ArtificialIntelligence #DeepLearning #ReinforcementLearning
Dimitri Bertsekas: https://www.youtube.com/playlist?list=PLmH30BG15SIp79JRJ-MVF12uvB1qPtPzn
#ArtificialIntelligence #DeepLearning #ReinforcementLearning
YouTube
Reinforcement Learning Course at ASU, Spring, 2021
Share your videos with friends, family, and the world
Coding TensorFlow
Laurence Moroney: https://www.youtube.com/playlist?list=PLQY2H8rRoyvwLbzbnKJ59NkZvQAW9wLbx
#ArtificialIntelligence #DeepLearning #Tensorflow
Laurence Moroney: https://www.youtube.com/playlist?list=PLQY2H8rRoyvwLbzbnKJ59NkZvQAW9wLbx
#ArtificialIntelligence #DeepLearning #Tensorflow
YouTube
Coding TensorFlow
Welcome to Coding TensorFlow! In this series, we will look at various parts of TensorFlow from a coding perspective. Subscribe to TensorFlow → https://goo.gl...
CS224W: Machine Learning with Graphs
Stanford / Winter 2021 [slides] pdf
https://web.stanford.edu/class/cs224w/
#machinelearning #graphs
Stanford / Winter 2021 [slides] pdf
https://web.stanford.edu/class/cs224w/
#machinelearning #graphs
Stanford CS330: Multi-Task and Meta-Learning, 2019
Lecture videos, Finn et al.: https://youtube.com/playlist?list=PLoROMvodv4rMC6zfYmnD7UG3LVvwaITY5
#ArtificialIntelligence #DeepLearning #MetaLearning
Lecture videos, Finn et al.: https://youtube.com/playlist?list=PLoROMvodv4rMC6zfYmnD7UG3LVvwaITY5
#ArtificialIntelligence #DeepLearning #MetaLearning
YouTube
Stanford CS330: Deep Multi-Task and Meta Learning
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai
Evading the Simplicity Bias: Training a Diverse Set of Models Discovers Solutions with Superior OOD Generalization
Teney et al.: https://arxiv.org/abs/2105.05612
#MachineLearning #DeepLearning #ArtificialIntelligence
Teney et al.: https://arxiv.org/abs/2105.05612
#MachineLearning #DeepLearning #ArtificialIntelligence
Deep learning for ai
By Yann lecun and Geoffrey Hinton and Yoshua bengio
https://vimeo.com/554817366
By Yann lecun and Geoffrey Hinton and Yoshua bengio
https://vimeo.com/554817366
Vimeo
Deep Learning for AI
Yoshua Bengio, Yann LeCun, and Geoffrey Hinton discuss "Deep Learning for AI," their Turing Lecture, a Contributed Article in the July 2021 CACM (https://cacm.acm.org/magazines/2021/7/253464)
Andrej Karpathy from Tesla is talking about Vision only autonomous driving.
https://www.youtube.com/watch?v=NSDTZQdo6H8&ab_channel=YarrowB.
https://www.youtube.com/watch?v=NSDTZQdo6H8&ab_channel=YarrowB.
YouTube
Andrej Karpathy (Tesla): CVPR 2021 (see description for better quality version)
Better quality version: https://youtu.be/g6bOwQdCJrc
Explaining Deep Neural Networks
Oana-Maria Camburu: https://arxiv.org/abs/2010.01496
#ArtificialIntelligence #DeepLearning #NeuralNetworks
Oana-Maria Camburu: https://arxiv.org/abs/2010.01496
#ArtificialIntelligence #DeepLearning #NeuralNetworks
As part of the Turing Lecture series for ACM's flagship publication, 2018 Turing Award laureates Yoshua Bengio, Yann Lecun, and Geoffrey Hinton discuss the current challenges and the future of deep learning: https://cacm.acm.org/magazines/2021/7/253464-deep-learning-for-ai/fulltext#R70
To watch the video: https://vimeo.com/user4730653
To watch the video: https://vimeo.com/user4730653
cacm.acm.org
Deep Learning for AI
How can neural networks learn the rich internal representations required for difficult tasks such as recognizing objects or understanding language?
Physics-based Deep Learning
Thuerey et al.: https://arxiv.org/abs/2109.05237
#MachineLearning #DeepLearning #Physics
Thuerey et al.: https://arxiv.org/abs/2109.05237
#MachineLearning #DeepLearning #Physics
YOLOP: You Only Look Once for Panoptic Driving Perception
Wu et al.: https://arxiv.org/abs/2108.11250
#ArtificialIntelligence #DeepLearning #MachineLearning
Wu et al.: https://arxiv.org/abs/2108.11250
#ArtificialIntelligence #DeepLearning #MachineLearning
2021 DeepMind x UCL Reinforcement Learning Lecture Series
Taught by DeepMind researchers, this series was created in collaboration with University College London (UCL) to offer students a comprehensive introduction to modern reinforcement learning.
Playlist
https://youtube.com/playlist?list=PLki3HkfgNEsKiZXMoYlR-14r1t_MAS7M8
https://youtu.be/_DpLWBG_nvk
#MachineLearning #artificialintelligence #deeplearning #computervision #MontrealAI
Taught by DeepMind researchers, this series was created in collaboration with University College London (UCL) to offer students a comprehensive introduction to modern reinforcement learning.
Playlist
https://youtube.com/playlist?list=PLki3HkfgNEsKiZXMoYlR-14r1t_MAS7M8
https://youtu.be/_DpLWBG_nvk
#MachineLearning #artificialintelligence #deeplearning #computervision #MontrealAI
COURSE
Introduction to Deep Learning (I2DL) (IN2346)
Lecturer: Prof. Dr. Matthias Niessner
TUM Visual Computing Group
https://niessner.github.io/I2DL/
Introduction to Deep Learning (I2DL) (IN2346)
Lecturer: Prof. Dr. Matthias Niessner
TUM Visual Computing Group
https://niessner.github.io/I2DL/