Using Deep Learning and TensorFlow Object Detection API for Corrosion Detection and Localization
https://blog.floydhub.com/localize-and-detect-corrosion-with-tensorflow-object-detection-api/
https://blog.floydhub.com/localize-and-detect-corrosion-with-tensorflow-object-detection-api/
FloydHub Blog
Using TensorFlow Object Detection API for Corrosion Detection and Localization
While computer vision techniques have been used with limited success for detecting corrosion from images, Deep Learning has opened up whole new possibilities
Discrete Flows: Invertible Generative Models of Discrete Data
Tran et al.: https://openreview.net/forum?id=rJlo4UIt_E
#ArtificialIntelligence #DeepLearning #GenerativeModels
Tran et al.: https://openreview.net/forum?id=rJlo4UIt_E
#ArtificialIntelligence #DeepLearning #GenerativeModels
openreview.net
Discrete Flows: Invertible Generative Models of Discrete Data
While normalizing flows have led to significant advances in modeling high-dimensional continuous distributions, their applicability to discrete distributions remains unknown. In this paper, we show...
Giovani in azione: Mirco Ravanelli – Di Astrid Panizza
12/05/2019
Sulla strada dei cervelli in fuga: dal Trentino al Canada per ricerche sull’intelligenza artificiale
https://www.ladigetto.it/rubriche/giovani_in_azione/87204-giovani-in-azione%3A-mirco-ravanelli-%E2%80%93-di-astrid-panizza.html
12/05/2019
Sulla strada dei cervelli in fuga: dal Trentino al Canada per ricerche sull’intelligenza artificiale
https://www.ladigetto.it/rubriche/giovani_in_azione/87204-giovani-in-azione%3A-mirco-ravanelli-%E2%80%93-di-astrid-panizza.html
ICLR 2019 posters
By Jonathan Binas and Avital Oliver: https://postersession.ai
#deeplearning #ICLR2019 #technology
By Jonathan Binas and Avital Oliver: https://postersession.ai
#deeplearning #ICLR2019 #technology
"Cellular automata as convolutional neural networks"
By William Gilpin: https://arxiv.org/abs/1809.02942
#CellularAutomata #NeuralNetworks #NeuralComputing #EvolutionaryComputing #ComputationalPhysics
By William Gilpin: https://arxiv.org/abs/1809.02942
#CellularAutomata #NeuralNetworks #NeuralComputing #EvolutionaryComputing #ComputationalPhysics
arXiv.org
Cellular automata as convolutional neural networks
Deep learning techniques have recently demonstrated broad success in predicting complex dynamical systems ranging from turbulence to human speech, motivating broader questions about how neural...
Machine Learning in High Energy Physics Community White Paper
Albertsson et al.: https://arxiv.org/abs/1807.02876
#machinelearning #physics #technology
Albertsson et al.: https://arxiv.org/abs/1807.02876
#machinelearning #physics #technology
arXiv.org
Machine Learning in High Energy Physics Community White Paper
Machine learning has been applied to several problems in particle physics research, beginning with applications to high-level physics analysis in the 1990s and 2000s, followed by an explosion of...
Playing Atari with Six Neurons
Cuccu et al.: https://arxiv.org/abs/1806.01363
#MachineLearning #ArtificialIntelligence #EvolutionaryComputing
Cuccu et al.: https://arxiv.org/abs/1806.01363
#MachineLearning #ArtificialIntelligence #EvolutionaryComputing
arXiv.org
Playing Atari with Six Neurons
Deep reinforcement learning, applied to vision-based problems like Atari games, maps pixels directly to actions; internally, the deep neural network bears the responsibility of both extracting...
Machine Learning in High Energy Physics Community White Paper
Albertsson et al.: https://arxiv.org/abs/1807.02876
#machinelearning #physics #technology
Albertsson et al.: https://arxiv.org/abs/1807.02876
#machinelearning #physics #technology
arXiv.org
Machine Learning in High Energy Physics Community White Paper
Machine learning has been applied to several problems in particle physics research, beginning with applications to high-level physics analysis in the 1990s and 2000s, followed by an explosion of...
A New Confidence Interval for the Mean of a Bounded Random Variable
Erik Learned-Miller and Philip S. Thomas: https://arxiv.org/abs/1905.06208
#Statistics #MachineLearning #Probability
Erik Learned-Miller and Philip S. Thomas: https://arxiv.org/abs/1905.06208
#Statistics #MachineLearning #Probability
How to (Properly) Evaluate Cross-Lingual Word Embeddings: On Strong Baselines, Comparative Analyses, and Some Misconceptions
Glavas et al.: https://arxiv.org/abs/1902.00508
#ArtificialIntelligence #MachineLearning #NaturalLanguageProcessing
Glavas et al.: https://arxiv.org/abs/1902.00508
#ArtificialIntelligence #MachineLearning #NaturalLanguageProcessing
arXiv.org
How to (Properly) Evaluate Cross-Lingual Word Embeddings: On...
Cross-lingual word embeddings (CLEs) enable multilingual modeling of meaning
and facilitate cross-lingual transfer of NLP models. Despite their ubiquitous
usage in downstream tasks, recent...
and facilitate cross-lingual transfer of NLP models. Despite their ubiquitous
usage in downstream tasks, recent...
Geometric Deep Learning for Pose Estimation
Theory and Pytorch Implementation Tutorial to find Object Pose from Single Monocular Image
By Vaishak Kumar: https://towardsdatascience.com/geometric-deep-learning-for-pose-estimation-6af45da05922
#MachineLearning #ComputerVision #DeepLearning #Robotics #PoseEstimation
Theory and Pytorch Implementation Tutorial to find Object Pose from Single Monocular Image
By Vaishak Kumar: https://towardsdatascience.com/geometric-deep-learning-for-pose-estimation-6af45da05922
#MachineLearning #ComputerVision #DeepLearning #Robotics #PoseEstimation
Medium
Geometric Deep Learning for Pose Estimation
Theory and Pytorch Implementation Tutorial to find Object Pose from Single Monocular Image
Introducing FastBert — A simple Deep Learning library for BERT Models
Blog by Kaushal Trivedi: https://medium.com/huggingface/introducing-fastbert-a-simple-deep-learning-library-for-bert-models-89ff763ad384
#MachineLearning #ArtificialIntelligence #NLP #NaturalLanguageProcessing
Blog by Kaushal Trivedi: https://medium.com/huggingface/introducing-fastbert-a-simple-deep-learning-library-for-bert-models-89ff763ad384
#MachineLearning #ArtificialIntelligence #NLP #NaturalLanguageProcessing
Medium
Introducing FastBert — A simple Deep Learning library for BERT Models
A simple to use Deep Learning library to build and deploy BERT models
A Survey on Neural Architecture Search
Wistuba et al.: https://arxiv.org/abs/1905.01392
#MachineLearning #ComputerVision #EvolutionaryComputing
Wistuba et al.: https://arxiv.org/abs/1905.01392
#MachineLearning #ComputerVision #EvolutionaryComputing
Cellular automata as convolutional neural networks"
By William Gilpin: https://arxiv.org/abs/1809.02942
#CellularAutomata #NeuralNetworks #NeuralComputing #EvolutionaryComputing #ComputationalPhysics
By William Gilpin: https://arxiv.org/abs/1809.02942
#CellularAutomata #NeuralNetworks #NeuralComputing #EvolutionaryComputing #ComputationalPhysics
arXiv.org
Cellular automata as convolutional neural networks
Deep learning techniques have recently demonstrated broad success in predicting complex dynamical systems ranging from turbulence to human speech, motivating broader questions about how neural...
GAN Lab: Play with Generative Adversarial Networks (GANs) in your browser!
By created by Minsuk Kahng, Nikhil Thorat, Polo Chau, Fernanda Viégas, and Martin Wattenberg: https://poloclub.github.io/ganlab/
Research paper: https://minsuk.com/research/papers/kahng-ganlab-vast2018.pdf
#AI #ArtificialIntelligence #DeepLearning #GenerativeAdversarialNetworks
By created by Minsuk Kahng, Nikhil Thorat, Polo Chau, Fernanda Viégas, and Martin Wattenberg: https://poloclub.github.io/ganlab/
Research paper: https://minsuk.com/research/papers/kahng-ganlab-vast2018.pdf
#AI #ArtificialIntelligence #DeepLearning #GenerativeAdversarialNetworks
UC Berkeley Graduate Receives ACM Doctoral Dissertation Award
https://www.acm.org/media-center/2019/may/dissertation-award-2018
https://www.acm.org/media-center/2019/may/dissertation-award-2018
Deep Compressed Sensing
Wu et al.: https://arxiv.org/pdf/1905.06723.pdf
#deeplearning #generativeadversarialnetworks #technology
Wu et al.: https://arxiv.org/pdf/1905.06723.pdf
#deeplearning #generativeadversarialnetworks #technology