Machine Learning Top 10 Articles for the Past Month (v.June 2018)
❄️💦10 مقاله برتر یادگیری ماشین به انتخاب Mybridge در ماه گذشته
https://goo.gl/yTVtv1 @ArtificialIntelligenceArticles
❄️💦10 مقاله برتر یادگیری ماشین به انتخاب Mybridge در ماه گذشته
https://goo.gl/yTVtv1 @ArtificialIntelligenceArticles
Improving Language Understanding with Unsupervised Learning
Unsupervised pre-training + fine-tuning (NLP)
By Alec Radford : https://blog.openai.com/language-unsupervised/
https://t.iss.one/ArtificialIntelligenceArticles
Unsupervised pre-training + fine-tuning (NLP)
By Alec Radford : https://blog.openai.com/language-unsupervised/
https://t.iss.one/ArtificialIntelligenceArticles
Yann LeCun :
ConvNet outperforms human dermatologists for melanoma detection.
Dermatologists in level-II protocol:
- sensitivity: 88.9% (±9.6%, P = 0.19)
- specificity: 75.7% (±11.7%, P < 0.05).
ConvNet:
- sensitivity: 88.9%
- specificity: 82.5%
"Conclusions: For the first time we compared a CNN’s diagnostic performance with a large international group of 58 dermatologists, including 30 experts. Most dermatologists were outperformed by the CNN. Irrespective of any physicians’ experience, they may benefit from assistance by a CNN’s image classification"
paper : https://goo.gl/oybrZj
https://t.iss.one/ArtificialIntelligenceArticles
ConvNet outperforms human dermatologists for melanoma detection.
Dermatologists in level-II protocol:
- sensitivity: 88.9% (±9.6%, P = 0.19)
- specificity: 75.7% (±11.7%, P < 0.05).
ConvNet:
- sensitivity: 88.9%
- specificity: 82.5%
"Conclusions: For the first time we compared a CNN’s diagnostic performance with a large international group of 58 dermatologists, including 30 experts. Most dermatologists were outperformed by the CNN. Irrespective of any physicians’ experience, they may benefit from assistance by a CNN’s image classification"
paper : https://goo.gl/oybrZj
https://t.iss.one/ArtificialIntelligenceArticles
OUP Academic
Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition…
AbstractBackground. Deep learning convolutional neural networks (CNN) may facilitate melanoma detection, but data comparing a CNN’s diagnostic performance to l
پژوهشگران دانشگاه امآیتی موفق شدهاند با استفاده از هوش مصنوعی و امواج فرکانس رادیویی حرکات فیزیکی انسان رو از پشت دیوار تشخیص دهند
Artificial intelligence senses people through walls
Wireless smart-home system from the Computer Science and Artificial Intelligence Laboratory could monitor diseases and help the elderly “age in place.”
https://news.mit.edu/2018/artificial-intelligence-senses-people-through-walls-0612
paper: https://openaccess.thecvf.com/content_cvpr_2018/CameraReady/2406.pdf
https://t.iss.one/ArtificialIntelligenceArticles
Artificial intelligence senses people through walls
Wireless smart-home system from the Computer Science and Artificial Intelligence Laboratory could monitor diseases and help the elderly “age in place.”
https://news.mit.edu/2018/artificial-intelligence-senses-people-through-walls-0612
paper: https://openaccess.thecvf.com/content_cvpr_2018/CameraReady/2406.pdf
https://t.iss.one/ArtificialIntelligenceArticles
MIT News
Artificial intelligence senses people through walls
RF-Pose, a wireless smart-home system from the MIT Computer Science and Artificial Intelligence Laboratory, could monitor diseases and help the elderly “age in place.”
AI can now generate memes
Abel L Peirson V & E Meltem Tolunay:
Dank Learning. Generating Memes Using Deep Neural Networks
https://arxiv.org/abs/1806.04510 @ArtificialIntelligenceArticles
Abel L Peirson V & E Meltem Tolunay:
Dank Learning. Generating Memes Using Deep Neural Networks
https://arxiv.org/abs/1806.04510 @ArtificialIntelligenceArticles
Self-supervisory Signals for Object Discovery and Detection. https://arxiv.org/abs/1806.03370 @ArtificialIntelligenceArticles
Altered Fingerprints: Detection and Localization
Achieves a True Detection Rate (TDR) of 99.24% at a False Detection Rate (FDR) of 2%, outperforming published results
https://arxiv.org/abs/1805.0091
Achieves a True Detection Rate (TDR) of 99.24% at a False Detection Rate (FDR) of 2%, outperforming published results
https://arxiv.org/abs/1805.0091
AI could get 100 times more energy-efficient with IBM’s new artificial synapses
Copying the features of a neural network in silicon might make machine learning more usable on small devices like smartphones.
https://goo.gl/hFfg69
paper : https://goo.gl/xyXbWo
https://t.iss.one/ArtificialIntelligenceArticles
Copying the features of a neural network in silicon might make machine learning more usable on small devices like smartphones.
https://goo.gl/hFfg69
paper : https://goo.gl/xyXbWo
https://t.iss.one/ArtificialIntelligenceArticles
MIT Technology Review
AI could get 100 times more energy-efficient with IBM’s new artificial synapses
Copying the features of a neural network in silicon might make machine learning more usable on small devices like smartphones.
مقاله جدیدی از پروفسور Li Fei-Fei
new paper : Li Fei-Fei
Learning to Decompose and Disentangle Representations for Video Prediction. https://arxiv.org/abs/1806.04166 @ArtificialIntelligenceArticles
new paper : Li Fei-Fei
Learning to Decompose and Disentangle Representations for Video Prediction. https://arxiv.org/abs/1806.04166 @ArtificialIntelligenceArticles
vulnerabilities in #deeplearning could lead to new kinds of healthcare fraud and other issues https://goo.gl/JBktiY @ArtificialIntelligenceArticles
Generating NES music using deep learning
Code : https://github.com/chrisdonahue/nesmdb
Paper: https://arxiv.org/abs/1806.04278 @ArtificialIntelligenceArticles
Code : https://github.com/chrisdonahue/nesmdb
Paper: https://arxiv.org/abs/1806.04278 @ArtificialIntelligenceArticles
A nice review article about relational reasoning, relational inductive biases in typical deep learning building blocks, and graph networks. https://arxiv.org/abs/1806.01261 @ArtificialIntelligenceA
Theoretical Impediments to Machine Learning With Seven Sparks from the Causal Revolution": Judea Pearl presents seven tasks which he claims are beyond reach of current machine learning systems but have been accomplished using the tools of causal modeling.
https://arxiv.org/abs/1801.04016
https://t.iss.one/ArtificialIntelligenceArticles
https://arxiv.org/abs/1801.04016
https://t.iss.one/ArtificialIntelligenceArticles
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2. Machine Learning
3. Deep Learning
4. #DataScience
5. #Neuroscience
6. #ResearchPapers
7. Related Courses and Ebooks
مقاله ی از دکتر علی اسلامی محقق Google DeepMind
https://deepmind.com/blog/neural-scene-representation-and-rendering/
paper :https://science.sciencemag.org/content/360/6394/1204
https://deepmind.com/blog/neural-scene-representation-and-rendering/
paper :https://science.sciencemag.org/content/360/6394/1204
Instant 3D Photography
Hedman et al.: https://visual.cs.ucl.ac.uk/pubs/instant3d/ @ArtificialIntelligenceArticles
Hedman et al.: https://visual.cs.ucl.ac.uk/pubs/instant3d/ @ArtificialIntelligenceArticles
🚀 100 Times Faster Natural Language Processing in Python
https://goo.gl/vX9zea
https://t.iss.one/ArtificialIntelligenceArticles
https://goo.gl/vX9zea
https://t.iss.one/ArtificialIntelligenceArticles
Medium
🚀 100 Times Faster Natural Language Processing in Python
How to take advantage of spaCy & a bit of Cython for blazing fast NLP
IBM researchers use analog memory to train deep NeuralNetworks faster than with GPUs, using hundreds of times less energy: https://goo.gl/jB4BWW paper : https://goo.gl/u1EE6C
NCRF++: An Open-source Neural Sequence Labeling Toolkit
GitHub : https://github.com/jiesutd/NCRFpp
paper : https://arxiv.org/abs/1806.05626 @ArtificialIntelligenceArticles
GitHub : https://github.com/jiesutd/NCRFpp
paper : https://arxiv.org/abs/1806.05626 @ArtificialIntelligenceArticles
End-to-End Parkinson Disease Diagnosis using Brain MR-Images by 3D-CNN. https://arxiv.org/abs/1806.05233 @ArtificialIntelligenceArticles
Deep Video Portraits
Photo-realistic reanimation of portrait videos. Transfer full 3D head pose, facial expression, eye gaze and blinking.
ArXiv
https://arxiv.org/abs/1805.11714
Full Demo
https://www.youtube.com/watch?v=qc5P2bvfl44
https://t.iss.one/ArtificialIntelligenceArticles
Photo-realistic reanimation of portrait videos. Transfer full 3D head pose, facial expression, eye gaze and blinking.
ArXiv
https://arxiv.org/abs/1805.11714
Full Demo
https://www.youtube.com/watch?v=qc5P2bvfl44
https://t.iss.one/ArtificialIntelligenceArticles
YouTube
Deep Video Portraits - SIGGRAPH 2018
H. Kim, P. Garrido , A. Tewari, W. Xu, J. Thies, M. Nießner, P. Pérez, C. Richardt, Michael Zollhöfer, C. Theobalt, Deep Video Portraits, ACM Transactions on Graphics (SIGGRAPH 2018)
We present a novel approach that enables photo-realistic re-animation…
We present a novel approach that enables photo-realistic re-animation…