Indoor SfMLearner
The unsupervised depth estimation task in indoor environments.
Github: https://github.com/svip-lab/Indoor-SfMLearner
Paper: https://arxiv.org/abs/2007.07696v1
The unsupervised depth estimation task in indoor environments.
Github: https://github.com/svip-lab/Indoor-SfMLearner
Paper: https://arxiv.org/abs/2007.07696v1
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Real Time Object Measurement
Object measurement using OpenCV and Python. We will use an A4 paper as our guide and find the width and height of objects.
https://www.murtazahassan.com/real-time-object-measurement/
Object measurement using OpenCV and Python. We will use an A4 paper as our guide and find the width and height of objects.
https://www.murtazahassan.com/real-time-object-measurement/
Accelerating 3D Deep Learning with PyTorch3D
PyTorch3D provides efficient, reusable components for 3D Computer Vision research with PyTorch.
Code: https://github.com/facebookresearch/pytorch3d
Paper: https://arxiv.org/abs/2007.08501v1
Mesh R-CNN: https://github.com/facebookresearch/meshrcnn
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PyTorch3D provides efficient, reusable components for 3D Computer Vision research with PyTorch.
Code: https://github.com/facebookresearch/pytorch3d
Paper: https://arxiv.org/abs/2007.08501v1
Mesh R-CNN: https://github.com/facebookresearch/meshrcnn
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GitHub
GitHub - facebookresearch/pytorch3d: PyTorch3D is FAIR's library of reusable components for deep learning with 3D data
PyTorch3D is FAIR's library of reusable components for deep learning with 3D data - facebookresearch/pytorch3d
Real-Time Face Mask Detector with Python, OpenCV, Keras
https://data-flair.training/blogs/face-mask-detection-with-python/
Dataset: https://data-flair.training/blogs/download-face-mask-data/
Code: https://data-flair.training/blogs/download-face-mask-detector-project-source-code/
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https://data-flair.training/blogs/face-mask-detection-with-python/
Dataset: https://data-flair.training/blogs/download-face-mask-data/
Code: https://data-flair.training/blogs/download-face-mask-detector-project-source-code/
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DataFlair
Real-Time Face Mask Detector with Python, OpenCV, Keras - DataFlair
Real-time Face Mask Detector with Python - develop a real-time system to detect whether the person on the webcam is wearing a mask or not. We train the face mask detection model using Keras and OpenCV.
Multi-scale Interactive Network for Salient Object Detection.
Github: https://github.com/lartpang/MINet
Paper: https://arxiv.org/abs/2007.09062v1
Results & Pretrained Parameters: https://drive.google.com/drive/folders/16yTcf_m-ehnhWgXlN6hbZpBKMy6lYIQQ
Github: https://github.com/lartpang/MINet
Paper: https://arxiv.org/abs/2007.09062v1
Results & Pretrained Parameters: https://drive.google.com/drive/folders/16yTcf_m-ehnhWgXlN6hbZpBKMy6lYIQQ
Private prediction methods: A systematic study by Facebook Research
https://ai.facebook.com/blog/private-prediction-methods-a-systematic-study/
Github: https://github.com/facebookresearch/private_prediction
Paper: https://arxiv.org/pdf/2007.05089.pdf
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https://ai.facebook.com/blog/private-prediction-methods-a-systematic-study/
Github: https://github.com/facebookresearch/private_prediction
Paper: https://arxiv.org/pdf/2007.05089.pdf
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Meta
Private prediction methods: A systematic study
The first systematic study of the performance of all main private prediction techniques in realistic machine learning (ML) scenarios. This study is meant to help solve…
❤1
Using Snorkel and NLP Models to Predict Multiple Sclerosis Severity Scores
https://www.kdnuggets.com/2020/07/labelling-data-using-snorkel.html
Tutorial: https://nlp4h.com/blog/snorkel_tutorial/
https://www.kdnuggets.com/2020/07/labelling-data-using-snorkel.html
Tutorial: https://nlp4h.com/blog/snorkel_tutorial/
KDnuggets
Labelling Data Using Snorkel - KDnuggets
In this tutorial, we walk through the process of using Snorkel to generate labels for an unlabelled dataset. We will provide you examples of basic Snorkel components by guiding you through a real clinical application of Snorkel.
Whole-Body Human Pose Estimation in the Wild
Github: https://github.com/jin-s13/COCO-WholeBody
Paper: https://arxiv.org/abs/2007.11858v1
Dataset: https://cocodataset.org/#keypoints-2017
Github: https://github.com/jin-s13/COCO-WholeBody
Paper: https://arxiv.org/abs/2007.11858v1
Dataset: https://cocodataset.org/#keypoints-2017
LOOCV for Evaluating Machine Learning Algorithms
https://machinelearningmastery.com/loocv-for-evaluating-machine-learning-algorithms/
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https://machinelearningmastery.com/loocv-for-evaluating-machine-learning-algorithms/
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DeepSVG
A Hierarchical Generative Network for Vector Graphics Animation.
https://blog.alexandrecarlier.com/deepsvg/
Github: https://github.com/alexandre01/deepsvg
Paper: https://arxiv.org/abs/2007.11301
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A Hierarchical Generative Network for Vector Graphics Animation.
https://blog.alexandrecarlier.com/deepsvg/
Github: https://github.com/alexandre01/deepsvg
Paper: https://arxiv.org/abs/2007.11301
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GitHub
GitHub - alexandre01/deepsvg: [NeurIPS 2020] Official code for the paper "DeepSVG: A Hierarchical Generative Network for Vector…
[NeurIPS 2020] Official code for the paper "DeepSVG: A Hierarchical Generative Network for Vector Graphics Animation". Includes a PyTorch library for deep learning with SVG data. ...
TensorFlow 2.3.0 Release
TensorFlow 2.3 has been released!
https://blog.tensorflow.org/2020/07/whats-new-in-tensorflow-2-3.html
Release : https://github.com/tensorflow/tensorflow/releases
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TensorFlow 2.3 has been released!
https://blog.tensorflow.org/2020/07/whats-new-in-tensorflow-2-3.html
Release : https://github.com/tensorflow/tensorflow/releases
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blog.tensorflow.org
What's new in TensorFlow 2.3?
TensorFlow 2.3 has been released with new tools to make it easier to load and preprocess data, and solve input-pipeline bottlenecks.
👶 BabyAI 1.1
BabyAI is a platform used to study the sample efficiency of grounded language acquisitio
Github: https://github.com/mila-iqia/babyai
https://github.com/mila-iqia/babyai
Paper: https://arxiv.org/abs/2007.12770v1
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BabyAI is a platform used to study the sample efficiency of grounded language acquisitio
Github: https://github.com/mila-iqia/babyai
https://github.com/mila-iqia/babyai
Paper: https://arxiv.org/abs/2007.12770v1
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GitHub
GitHub - mila-iqia/babyai: BabyAI platform. A testbed for training agents to understand and execute language commands.
BabyAI platform. A testbed for training agents to understand and execute language commands. - mila-iqia/babyai
Building a Content-Based Book Recommendation Engine
https://www.kdnuggets.com/2020/07/building-content-based-book-recommendation-engine.html
Content-Based Recommendation System using Word Embeddings: https://medium.com/towards-artificial-intelligence/content-based-recommendation-system-using-word-embeddings-c1c15de1ef95
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https://www.kdnuggets.com/2020/07/building-content-based-book-recommendation-engine.html
Content-Based Recommendation System using Word Embeddings: https://medium.com/towards-artificial-intelligence/content-based-recommendation-system-using-word-embeddings-c1c15de1ef95
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KDnuggets
Building a Content-Based Book Recommendation Engine
In this blog, we will see how we can build a simple content-based recommender system using Goodreads data.
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SipMask: Spatial Information Preservation for Fast Image and Video Instance Segmentation
Github: https://github.com/JialeCao001/SipMask
Paper: https://arxiv.org/abs/2007.14772v1
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Github: https://github.com/JialeCao001/SipMask
Paper: https://arxiv.org/abs/2007.14772v1
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On the Convergence of Tsetlin Machines for the IDENTITY- and NOT Operators
The Tsetlin Machine solves complex pattern recognition problems with easy-to-interpret propositional formulas.
Github: https://github.com/cair/TsetlinMachine
Paper: https://arxiv.org/abs/2007.14268v1
The Tsetlin Machine solves complex pattern recognition problems with easy-to-interpret propositional formulas.
Github: https://github.com/cair/TsetlinMachine
Paper: https://arxiv.org/abs/2007.14268v1
Train your TensorFlow model on Google Cloud using TensorFlow Cloud
https://blog.tensorflow.org/2020/08/train-your-tensorflow-model-on-google.html
https://blog.tensorflow.org/2020/08/train-your-tensorflow-model-on-google.html
blog.tensorflow.org
Train your TensorFlow model on Google Cloud using TensorFlow Cloud
The TensorFlow Cloud repository provides APIs that will allow you to easily go from debugging and training your Keras and TensorFlow code in a local environment to distributed training in the cloud.
How to Use XGBoost for Time Series Forecasting
https://machinelearningmastery.com/xgboost-for-time-series-forecasting/
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https://machinelearningmastery.com/xgboost-for-time-series-forecasting/
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Netflix’s Polynote is a New Open Source Framework to Build Better Data Science Notebooks
Polynote is an experimental polyglot notebook environment. Currently, it supports Scala and Python, SQL, and Vega.
https://www.kdnuggets.com/2020/08/netflix-polynote-open-source-framework-better-data-science-notebooks.html
Project page: https://polynote.org/
Github: https://github.com/polynote/polynote
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Polynote is an experimental polyglot notebook environment. Currently, it supports Scala and Python, SQL, and Vega.
https://www.kdnuggets.com/2020/08/netflix-polynote-open-source-framework-better-data-science-notebooks.html
Project page: https://polynote.org/
Github: https://github.com/polynote/polynote
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Multilingual Speech Synthesis
Synthesized samples, training and evaluation data, source code, and parameters for Multilingual Speech Synthesis.
Github: https://github.com/Tomiinek/Multilingual_Text_to_Speech
Demo Code: https://colab.research.google.com/github/Tomiinek/Multilingual_Text_to_Speech/blob/master/notebooks/code_switching_demo.ipynb
Website with samples: https://tomiinek.github.io/multilingual_speech_samples/
Paper: https://arxiv.org/abs/2008.00768
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Synthesized samples, training and evaluation data, source code, and parameters for Multilingual Speech Synthesis.
Github: https://github.com/Tomiinek/Multilingual_Text_to_Speech
Demo Code: https://colab.research.google.com/github/Tomiinek/Multilingual_Text_to_Speech/blob/master/notebooks/code_switching_demo.ipynb
Website with samples: https://tomiinek.github.io/multilingual_speech_samples/
Paper: https://arxiv.org/abs/2008.00768
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Metrics to Use to Evaluate Deep Learning Object Detectors.
https://www.kdnuggets.com/2020/08/metrics-evaluate-deep-learning-object-detectors.html
A Survey on Performance Metrics for Object-Detection Algorithms: https://www.researchgate.net/publication/343194514_A_Survey_on_Performance_Metrics_for_Object-Detection_Algorithms
Github: https://github.com/ultralytics/yolov3/issues/898
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https://www.kdnuggets.com/2020/08/metrics-evaluate-deep-learning-object-detectors.html
A Survey on Performance Metrics for Object-Detection Algorithms: https://www.researchgate.net/publication/343194514_A_Survey_on_Performance_Metrics_for_Object-Detection_Algorithms
Github: https://github.com/ultralytics/yolov3/issues/898
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