Style Transfer Tutorial
Colab: https://colab.research.google.com/github/tensorflow/docs/blob/master/site/en/r2/tutorials/generative/style_transfer.ipynb
#ArtificialIntelligence #DeepLearning #MachineLearning

These are seven ways Google’s image analysis tools classifies uploaded images:
Faces
Objects
Labels
Web Entities
Text
Properties
Safe Search

https://www.searchenginejournal.com/google-cloud-vision-tool/304237/

In medical imaging, computer aided detection (CAD) systems are available for detection of tumors and diagnosis of diseases from images acquired by imaging modalities like CT, MRI, X-ray and ultrasound. AI techniques used in computer vision such as object detection and segmentation offer unique possibilities to help radiologists make diagnosis faster and more accurately, leading to prioritization of cases, better patient care, and reduction in cost.

DNN Architecture for High Performance Prediction on Natural Videos Loses Submodule's Abil... https://arxiv.org/abs/1904.07969

A Comprehensive Study of Alzheimer's Disease Classification Using Convolutional Neural Ne... https://arxiv.org/abs/1904.07950

IAN: Combining Generative Adversarial Networks for Imaginative Face Generation. https://arxiv.org/abs/1904.07916

Learning Probabilistic Multi-Modal Actor Models for Vision-Based Robotic Grasping. https://arxiv.org/abs/1904.07319

A new deep learning model developed by NVIDIA Research can turn rough doodles into photorealistic masterpieces with breathtaking ease. GauGAN converts segmentation maps into stunning lifelike images. https://bit.ly/2ugUJtv #gaugan #nvidia #deeplearning

Did you know that the now famous blackhole image was processed in Python? The code is on github if you are interested to have a poke around. Remember, these are scientists not programmers so it is not all flawless code; maybe you can find some ways to improve the code? :)

https://github.com/achael/eht-imaging

All videos & slides from #ScaledML2019:


https://www.youtube.com/playlist?list=PLRM2gQVaW_wWXoUnSfZTxpgDmNaAS1RtG

Representer Point Selection for Explaining Deep Neural Networks by Joon Sik Kim & Chih-Kuan Yeh, #mldcmu

Why did a Deep Neural Network #DNN make a certain prediction

Learn more: https://blog.ml.cmu.edu/2019/04/19/representer-point-selection-explain-dnn/

#AI #machinelearning #deeplearning #ML

If you are interested in doing a PhD in Machine Learning (deep learning/deep RL) while drawing inspiration from neuroscience, consider this position https://sites.google.com/corp/view/razp/announcement

Artificial Intelligence & #Neuroscience: A Virtuous Circle https://deepmind.com/blog/ai-and-neuroscience-virtuous-circle/

Yes, We Can Now Construct Speech from Brain Waves. # #BigData #Analytics #DeepLearning #MachineLearning #DataScience #AI #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #VueJS #GoLang #Serverless #DataScientist #Linux #NeuroScience
https://www.biorxiv.org/content/10.1101/350124v2

The Machines That Will Read Your Mind: https://www.wsj.com/articles/the-machines-that-will-read-your-mind-11554476156

#AI #BigData #DataScience #MachineLearning #Neuroscience #NeuralNetworks #DeepLearning

New #deeplearning paper at the intersection of #AI #mathematics #psychology and #neuroscience: A mathematical theory of semantic development in deep neural networks: https://arxiv.org/abs/1810.10531

New preprint on state of the art #Deeplearning models of the retinal response to natural scenes; https://www.biorxiv.org/content/early/2018/06/08/340943 … The model's interior functionally matches that of the retina and it generalizes to capture decades of #neuroscience experiments on artificial stimuli

The Tracking Machine Learning challenge : Accuracy phase
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

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