A Gentle Introduction to Object Recognition With Deep Learning
https://machinelearningmastery.com/object-recognition-with-deep-learning/
https://machinelearningmastery.com/object-recognition-with-deep-learning/
Few-Shot Adversarial Learning of Realistic Neural Talking Head Models
Video: youtu.be/p1b5aiTrGzY
Paper: arxiv.org/abs/1905.08233
Video: youtu.be/p1b5aiTrGzY
Paper: arxiv.org/abs/1905.08233
YouTube
Few-Shot Adversarial Learning of Realistic Neural Talking Head Models
Statement regarding the purpose and effect of the technology
(NB: this statement reflects personal opinions of the authors and not of their organizations)
We believe that telepresence technologies in AR, VR and other media are to transform the world in the…
(NB: this statement reflects personal opinions of the authors and not of their organizations)
We believe that telepresence technologies in AR, VR and other media are to transform the world in the…
Data-Efficient Image Recognition with Contrastive Predictive Coding
Article: https://arxiv.org/abs/1905.09272
Article: https://arxiv.org/abs/1905.09272
arXiv.org
Data-Efficient Image Recognition with Contrastive Predictive Coding
Human observers can learn to recognize new categories of images from a handful of examples, yet doing so with artificial ones remains an open challenge. We hypothesize that data-efficient...
Moving Camera, Moving People: A Deep Learning Approach to Depth Prediction
http://ai.googleblog.com/2019/05/moving-camera-moving-people-deep.html
http://ai.googleblog.com/2019/05/moving-camera-moving-people-deep.html
research.google
Moving Camera, Moving People: A Deep Learning Approach to Depth Prediction
Posted by Tali Dekel, Research Scientist and Forrester Cole, Software Engineer, Machine Perception The human visual system has a remarkable abili...
How to Perform Object Detection in Photographs Using Mask R-CNN with Keras
https://machinelearningmastery.com/how-to-perform-object-detection-in-photographs-with-mask-r-cnn-in-keras/
https://machinelearningmastery.com/how-to-perform-object-detection-in-photographs-with-mask-r-cnn-in-keras/
TensorWatch: a debugging and visualization tool designed for deep learning
https://github.com/microsoft/tensorwatch
https://github.com/microsoft/tensorwatch
GitHub
GitHub - microsoft/tensorwatch: Debugging, monitoring and visualization for Python Machine Learning and Data Science
Debugging, monitoring and visualization for Python Machine Learning and Data Science - microsoft/tensorwatch
Estimators, Loss Functions, Optimizers —Core of ML Algorithms
https://towardsdatascience.com/estimators-loss-functions-optimizers-core-of-ml-algorithms-d603f6b0161a]
https://towardsdatascience.com/estimators-loss-functions-optimizers-core-of-ml-algorithms-d603f6b0161a]
Medium
Estimators, Loss Functions, Optimizers —Core of ML Algorithms
In order to understand how a machine learning algorithm learns from data to predict an outcome, it is essential to understand the…
Torchvision 0.3: segmentation, detection models, new datasets
https://pytorch.org/blog/torchvision03/
https://pytorch.org/blog/torchvision03/
COBRA: Data-Efficient Model-Based RL through Unsupervised Object Discovery and Curiosity-Driven Exploration
https://arxiv.org/abs/1905.09275
https://arxiv.org/abs/1905.09275
illustrated Artificial Intelligence cheatsheets covering the content of the CS 221 class
Link: https://stanford.edu/~shervine/teaching/cs-221/
Reflex-based models with Machine Learning: https://stanford.edu/~shervine/teaching/cs-221/cheatsheet-reflex-models
Link: https://stanford.edu/~shervine/teaching/cs-221/
Reflex-based models with Machine Learning: https://stanford.edu/~shervine/teaching/cs-221/cheatsheet-reflex-models
stanford.edu
Teaching - CS 221
Teaching page of Shervine Amidi, Graduate Student at Stanford University.
How degenerate is the parametrization of neural networks with the ReLU activation function?
https://arxiv.org/abs/1905.09803
https://arxiv.org/abs/1905.09803
How to Perform Object Detection With YOLOv3 in Keras
https://machinelearningmastery.com/how-to-perform-object-detection-with-yolov3-in-keras/
https://machinelearningmastery.com/how-to-perform-object-detection-with-yolov3-in-keras/
Forwarded from Artificial Intelligence
Unsupervised Learning with Graph Neural Networks
video: http://www.ipam.ucla.edu/programs/workshops/workshop-iv-deep-geometric-learning-of-big-data-and-applications/?tab=schedule
guide: http://helper.ipam.ucla.edu/publications/glws4/glws4_15546.pdf
video: http://www.ipam.ucla.edu/programs/workshops/workshop-iv-deep-geometric-learning-of-big-data-and-applications/?tab=schedule
guide: http://helper.ipam.ucla.edu/publications/glws4/glws4_15546.pdf
IPAM
Workshop IV: Deep Geometric Learning of Big Data and Applications - IPAM
Augmented Neural ODEs
Github: https://github.com/EmilienDupont/augmented-neural-odes
Article: https://arxiv.org/abs/1904.01681
Github: https://github.com/EmilienDupont/augmented-neural-odes
Article: https://arxiv.org/abs/1904.01681
GitHub
GitHub - EmilienDupont/augmented-neural-odes: Pytorch implementation of Augmented Neural ODEs :sunflower:
Pytorch implementation of Augmented Neural ODEs :sunflower: - EmilienDupont/augmented-neural-odes
SimpleSelfAttention
The purpose of this repository is two-fold:
-demonstrate improvements brought by the use of a self-attention layer in an image -classification model.
introduce a new layer which I call SimpleSelfAttention
https://github.com/sdoria/SimpleSelfAttention
The purpose of this repository is two-fold:
-demonstrate improvements brought by the use of a self-attention layer in an image -classification model.
introduce a new layer which I call SimpleSelfAttention
https://github.com/sdoria/SimpleSelfAttention
GitHub
GitHub - sdoria/SimpleSelfAttention: A simpler version of the self-attention layer from SAGAN, and some image classification results.
A simpler version of the self-attention layer from SAGAN, and some image classification results. - sdoria/SimpleSelfAttention
How to Train an Object Detection Model to Find Kangaroos in Photographs (R-CNN with Keras)
https://machinelearningmastery.com/how-to-train-an-object-detection-model-with-keras/
https://machinelearningmastery.com/how-to-train-an-object-detection-model-with-keras/
MachineLearningMastery.com
How to Train an Object Detection Model with Keras - MachineLearningMastery.com
Object detection is a challenging computer vision task that involves predicting both where the objects are in the image and what type of objects were detected. The Mask Region-based Convolutional Neural Network, or Mask R-CNN, model is one of the state-of…
EfficientNets
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
link: https://arxiv.org/abs/1905.11946.
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
link: https://arxiv.org/abs/1905.11946.
arXiv.org
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Convolutional Neural Networks (ConvNets) are commonly developed at a fixed resource budget, and then scaled up for better accuracy if more resources are available. In this paper, we systematically...
Multi-Sample Dropout for Accelerated Training and Better Generalization
Link: https://arxiv.org/abs/1905.09788
Link: https://arxiv.org/abs/1905.09788
arXiv.org
Multi-Sample Dropout for Accelerated Training and Better Generalization
Dropout is a simple but efficient regularization technique for achieving better generalization of deep neural networks (DNNs); hence it is widely used in tasks based on DNNs. During training,...
A Gentle Introduction to Deep Learning for Face Recognition
https://machinelearningmastery.com/introduction-to-deep-learning-for-face-recognition/
https://machinelearningmastery.com/introduction-to-deep-learning-for-face-recognition/
MachineLearningMastery.com
A Gentle Introduction to Deep Learning for Face Recognition - MachineLearningMastery.com
Face recognition is the problem of identifying and verifying people in a photograph by their face. It is a task that is trivially performed by humans, even under varying light and when faces are changed by age or obstructed with accessories and facial hair.…