The Tracking Machine Learning challenge : Accuracy phase
Amrouche et al.:https://arxiv.org/pdf/1904.06778v1.pdf
#ArtificialIntelligence #MachineLearning #Physics @ArtificialIntelligenceArticles
Amrouche et al.:https://arxiv.org/pdf/1904.06778v1.pdf
#ArtificialIntelligence #MachineLearning #Physics @ArtificialIntelligenceArticles
Robotics: Philosophy of Mind using a Screwdriver
https://sro.sussex.ac.uk/id/eprint/19622/
https://pdfs.semanticscholar.org/344b/dbe8dc852e49ad9e2b0ed44afbece8871b2c.pdf
https://sro.sussex.ac.uk/id/eprint/19622/
https://pdfs.semanticscholar.org/344b/dbe8dc852e49ad9e2b0ed44afbece8871b2c.pdf
Dynamic Gesture Recognition by Using CNNs and Star RGB: a Temporal Information Condensation. https://arxiv.org/abs/1904.08505
Learning 2D to 3D Lifting for Object Detection in 3D for Autonomous Vehicles. https://arxiv.org/abs/1904.08494
Understanding the Effectiveness of Ultrasonic Microphone Jammer. https://arxiv.org/abs/1904.08490
Machine Vision Guided 3D Medical Image Compression for Efficient Transmission and Accurat... https://arxiv.org/abs/1904.08487
Variational Prototyping-Encoder: One-Shot Learning with Prototypical Images. https://arxiv.org/abs/1904.08482
A large-scale field test on word-image classification in large historical document collec... https://arxiv.org/abs/1904.08421
Neural Painters: A learned differentiable constraint for generating brushstroke paintings. https://arxiv.org/abs/1904.08410
A Selective Overview of Deep Learning
Fan et al.: https://arxiv.org/abs/1904.05526
#ArtificialIntelligence #DeepLearning #MachineLearning
Fan et al.: https://arxiv.org/abs/1904.05526
#ArtificialIntelligence #DeepLearning #MachineLearning
MR-based CT Generation (DCCC) Tensorflow Project
This repository is the implementations of the paper "MR-based Synthetic CT Generation using Deep Convolutional Neural Network Method,"
https://github.com/ChengBinJin/MRI-to-CT-DCNN-TensorFlow
This repository is the implementations of the paper "MR-based Synthetic CT Generation using Deep Convolutional Neural Network Method,"
https://github.com/ChengBinJin/MRI-to-CT-DCNN-TensorFlow
Fooling automated surveillance cameras: adversarial patches to attack person detection"
Thys et al.: https://arxiv.org/abs/1904.08653
#ArtificialIntelligence #DeepLearning #MachineLearning
Thys et al.: https://arxiv.org/abs/1904.08653
#ArtificialIntelligence #DeepLearning #MachineLearning
CS294-158 Deep Unsupervised Learning SP19
https://www.youtube.com/channel/UCf4SX8kAZM_oGcZjMREsU9w/videos?fbclid=IwAR01HPq5VLKX8aXwFbB4UWs5mZVgOOYOLUpjx_O2015rso-7U_H32hu-AKE
https://www.youtube.com/channel/UCf4SX8kAZM_oGcZjMREsU9w/videos?fbclid=IwAR01HPq5VLKX8aXwFbB4UWs5mZVgOOYOLUpjx_O2015rso-7U_H32hu-AKE
Self-Attention Generative Adversarial Networks
Zhang et al.: https://arxiv.org/abs/1805.08318
#DeepLearning #GenerativeAdversarialNetworks #MachineLearning
Zhang et al.: https://arxiv.org/abs/1805.08318
#DeepLearning #GenerativeAdversarialNetworks #MachineLearning
Functional brain network architecture supporting the learning of social networks in humans @ArtificialIntelligenceArticles
Tompson et al.: https://psyarxiv.com/r46gj/
#brainnetworks #neuroscience #socialnetworks #neuralnetworks @ArtificialIntelligenceArticles
Tompson et al.: https://psyarxiv.com/r46gj/
#brainnetworks #neuroscience #socialnetworks #neuralnetworks @ArtificialIntelligenceArticles
Tesla’s new self-driving chip is here, and this is your best look yet
https://www.theverge.com/2019/4/22/18511594/tesla-new-self-driving-chip-is-here-and-this-is-your-best-look-yet
https://www.theverge.com/2019/4/22/18511594/tesla-new-self-driving-chip-is-here-and-this-is-your-best-look-yet
Linked Dynamic Graph CNN: Learning on Point Cloud via Linking Hierarchical Features
Zhang et al.: https://arxiv.org/abs/1904.10014
#ArtificialIntelligence #DeepLearning #MachineLearning
Zhang et al.: https://arxiv.org/abs/1904.10014
#ArtificialIntelligence #DeepLearning #MachineLearning
arXiv.org
Linked Dynamic Graph CNN: Learning on Point Cloud via Linking...
Learning on point cloud is eagerly in demand because the point cloud is a common type of geometric data and can aid robots to understand environments robustly. However, the point cloud is sparse,...