Deep Learning for Generic Object Detection: A Survey
paper : https://arxiv.org/abs/1809.02165v1
#computervision #deeplearning #patternrecognition @ArtificialIntelligenceArticles
paper : https://arxiv.org/abs/1809.02165v1
#computervision #deeplearning #patternrecognition @ArtificialIntelligenceArticles
Data Augmentation For Object Detection
tutorial articles : https://blog.paperspace.com/data-augmentation-for-bounding-boxes/
GitHub : https://github.com/Paperspace/DataAugmentationForObjectDetection/blob/master/quick-start.ipynb
#artificialintelligence #deeplearning #machinelearning
@ArtificialIntelligenceArticles
tutorial articles : https://blog.paperspace.com/data-augmentation-for-bounding-boxes/
GitHub : https://github.com/Paperspace/DataAugmentationForObjectDetection/blob/master/quick-start.ipynb
#artificialintelligence #deeplearning #machinelearning
@ArtificialIntelligenceArticles
Paperspace Blog
Data Augmentation For Bounding Boxes: Flipping
How to adapt major image augmentation techniques for object detection purposes. We also cover the implementation of horizontal flip augmentation.
Musical Neural Networks in the Browser
Slides by Tero Parviainen : https://teropa.info/wac2018 @ArtificialIntelligenceArticles
Slides by Tero Parviainen : https://teropa.info/wac2018 @ArtificialIntelligenceArticles
Introduction to astroML: Machine Learning for Astrophysics
VanderPlas et al.: https://arxiv.org/pdf/1411.5039.pdf
#astrophysics #deeplearning #machinelearning @ArtificialIntelligenceArticles
VanderPlas et al.: https://arxiv.org/pdf/1411.5039.pdf
#astrophysics #deeplearning #machinelearning @ArtificialIntelligenceArticles
Best paper award at #emnlp2018
"Phrase-Based & Neural Unsupervised Machine Translation"
Lample et al.: https://arxiv.org/abs/1804.07755
Code:
https://github.com/facebookresearch/UnsupervisedMT
Blog:
https://code.fb.com/ai-research/unsupervised-machine-translation-a-novel-approach-to-provide-fast-accurate-translations-for-more-languages/
#computation #deeplearning #language
https://t.iss.one/ArtificialIntelligenceArticles
"Phrase-Based & Neural Unsupervised Machine Translation"
Lample et al.: https://arxiv.org/abs/1804.07755
Code:
https://github.com/facebookresearch/UnsupervisedMT
Blog:
https://code.fb.com/ai-research/unsupervised-machine-translation-a-novel-approach-to-provide-fast-accurate-translations-for-more-languages/
#computation #deeplearning #language
https://t.iss.one/ArtificialIntelligenceArticles
GitHub
GitHub - facebookresearch/UnsupervisedMT: Phrase-Based & Neural Unsupervised Machine Translation
Phrase-Based & Neural Unsupervised Machine Translation - facebookresearch/UnsupervisedMT
A Connectome Based Hexagonal Lattice Convolutional Network Model of the Drosophila Visual System
David Tschopp et al.: https://arxiv.org/abs/1806.04793
#artificialintelligence #machinelearning #neuralnetworks
@ArtificialIntelligenceArticles
David Tschopp et al.: https://arxiv.org/abs/1806.04793
#artificialintelligence #machinelearning #neuralnetworks
@ArtificialIntelligenceArticles
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Cat-to-cat translation with pix2pix
Code : https://github.com/keijiro/Pix2Pix @ArtificialIntelligenceArticles
Code : https://github.com/keijiro/Pix2Pix @ArtificialIntelligenceArticles
On the Learning Dynamics of Deep Neural Networks.
Remi Tachet des Combes, Mohammad Pezeshki, Samira Shabanian, Aaron Courville, and Yoshua Bengio
https://arxiv.org/abs/1809.06848
@ArtificialIntelligenceArticles
Remi Tachet des Combes, Mohammad Pezeshki, Samira Shabanian, Aaron Courville, and Yoshua Bengio
https://arxiv.org/abs/1809.06848
@ArtificialIntelligenceArticles
Blake Richards: Deep Learning with Ensembles of Neocortical Microcircuits
An inspiring talk by Blake Richards at the ICLR2018 emphasizing the interaction between neuroscience and machine learning. This intersection is where great things happen.
https://goo.gl/1YCjrm
https://t.iss.one/ArtificialIntelligenceArticles
An inspiring talk by Blake Richards at the ICLR2018 emphasizing the interaction between neuroscience and machine learning. This intersection is where great things happen.
https://goo.gl/1YCjrm
https://t.iss.one/ArtificialIntelligenceArticles
YouTube
Blake Richards: Deep Learning with Ensembles of Neocortical Microcircuits (ICLR 2018 invited talks)
Abstract: Deep learning in artificial intelligence (AI) has demonstrated that learning hierarchical representations is a good approach for generating useful sensorimotor behaviors. However, the key to effective hierarchical learning is a mechanism for ""credit…
Seq2Seq-Vis: A Visual Debugging Tool for Sequence-to-Sequence Models
Strobelt et al.: https://seq2seq-vis.io
Strobelt et al.: https://seq2seq-vis.io
An online TensorFlow handbook (https://tf.wiki/ ) based on Eager Execution
(Both Chinese and English version are available online)
Open-sourced on GitHub : https://github.com/snowkylin/TensorFlow-cn
(Both Chinese and English version are available online)
Open-sourced on GitHub : https://github.com/snowkylin/TensorFlow-cn
Deep Reinforcement Learning
CS 294-112 at UC Berkeley | Instructor Sergey Levine
Lecture Slides : https://rail.eecs.berkeley.edu/deeprlcourse/
CS 294-112 at UC Berkeley | Instructor Sergey Levine
Lecture Slides : https://rail.eecs.berkeley.edu/deeprlcourse/
How to write a great research paper
چگونه یک مقاله خوب بنویسید تهیه شده توسط Nando de Freitas و شرکت DeepMind و دانشگاه نیویورک و....
https://goo.gl/HeanCW @ArtificialIntelligenceArticles
چگونه یک مقاله خوب بنویسید تهیه شده توسط Nando de Freitas و شرکت DeepMind و دانشگاه نیویورک و....
https://goo.gl/HeanCW @ArtificialIntelligenceArticles
ArtificialIntelligenceArticles
How to write a great research paper چگونه یک مقاله خوب بنویسید تهیه شده توسط Nando de Freitas و شرکت DeepMind و دانشگاه نیویورک و.... https://goo.gl/HeanCW @ArtificialIntelligenceArticles
YouTube
How to Write a Great Research Paper
Writing papers and giving talks are key skills for any researcher, but they aren’t easy. In this pair of presentations, I’ll describe simple guidelines that I follow for writing papers and giving talks, which I think may be useful to you too. I don’t have…
AI + Aerospace | Cosmology | Physics
A few useful references : https://goo.gl/gMQru4 #References
#aerospace #artificialintelligence #cosmology
A few useful references : https://goo.gl/gMQru4 #References
#aerospace #artificialintelligence #cosmology
Dynamical, symplectic and stochastic perspectives on optimization
Michael Jordan – ICM2018 : https://youtu.be/wXNWVhE2Dl4 @ArtificialIntelligenceArticles
Michael Jordan – ICM2018 : https://youtu.be/wXNWVhE2Dl4 @ArtificialIntelligenceArticles
The mathematics of machine learning and deep learning – Sanjeev Arora – ICM2018 https://goo.gl/vj2yCF @ArtificialIntelligenceArticles
Why building your own Deep Learning computer is 10x cheaper than AWS
https://goo.gl/4ZbUf8 @ArtificialIntelligenceArticles
https://goo.gl/4ZbUf8 @ArtificialIntelligenceArticles
Speech and Language Processing (3rd ed. draft)
Dan Jurafsky and James H. Martin : https://web.stanford.edu/~jurafsky/slp3/
Dan Jurafsky and James H. Martin : https://web.stanford.edu/~jurafsky/slp3/
Series of Jupyter Notebooks with step-by-step introduction to data science and machine learning
Code : https://github.com/rasbt/python-machine-learning-book-2nd-edition
Code : https://github.com/rasbt/python-machine-learning-book-2nd-edition
Computer Vision dataset search
visualdata.io is a great resource for exploring computer vision datasets : https://www.visualdata.io/
visualdata.io is a great resource for exploring computer vision datasets : https://www.visualdata.io/