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Getting Started with OpenCV CUDA Module

Valeriia Koriukina (xperience.ai)
September 15, 2020 Leave a Comment
how-to Image Processing OpenCV 4 Performance

September 15, 2020 By Leave a Comment

opencv-gpu-frontal-image

If you have been working with OpenCV for some time, you should have noticed that in most scenarios OpenCV utilizes CPU, which doesn't always guarantee you the desired performance. To tackle this ...

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Tags: Computer Vision CUDA Dense Optical Flow Farneback Optical Flow GPU OpenCV4 Optical Flow
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Filed Under: how-to, Image Processing, OpenCV 4, Performance

TensorBoard with PyTorch Lightning

Neelabh Madan (IIT Delhi)
August 10, 2020 Leave a Comment
Deep Learning how-to Image Classification Machine Learning PyTorch Tutorial

August 10, 2020 By Leave a Comment

A picture is worth a thousand words! As computer vision and machine learning experts, we could not agree more. Human intuition is the most powerful way of making sense out of random chaos, ...

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Tags: Comet Logger Computer Vision deep learning graphs Lightning logging Machine Learning MNIST Neptune Logger PyTorch tensorboard Tensorboard Logger tutorial visualisation
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Filed Under: Deep Learning, how-to, Image Classification, Machine Learning, PyTorch, Tutorial

Federated Learning using PyTorch and PySyft

Jatin Prakash
May 25, 2020 Leave a Comment
Deep Learning Image Classification PyTorch Tutorial

May 25, 2020 By Leave a Comment

This is a a gentle introduction to federated learning --- a technique that makes machine learning more secure by training on decentralized data. We will also cover a real-life example of federated ...

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Tags: Computer Vision deep learning federated learning MNIST privacy preserving pysyft PyTorch
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Filed Under: Deep Learning, Image Classification, PyTorch, Tutorial

Creating a Virtual Pen And Eraser with OpenCV

Taha Anwar ( BleedAI.com )
May 19, 2020 Leave a Comment
Application Image Processing OpenCV 4 Tracking Tutorial

May 19, 2020 By Leave a Comment

Wouldn't it be cool if you could just wave a pen in the air to draw something virtually and it actually draws it on the screen? It could be even more interesting if we didn't use any special hardware ...

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Tags: Computer Vision Image Processing OpenCV4 Python tutorial
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Filed Under: Application, Image Processing, OpenCV 4, Tracking, Tutorial

Getting Started with PyTorch Lightning

Neelabh Madan (IIT Delhi)
May 10, 2020 Leave a Comment
Deep Learning how-to Image Classification Machine Learning PyTorch Tutorial

May 10, 2020 By Leave a Comment

featured-lightning

Imagine, one day you have an amazing idea for your machine learning project. You write down all the details on a piece of paper- the model architecture, the optimizer, the dataset. And now you just ...

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Tags: Computer Vision deep learning Lightning Machine Learning MNIST PyTorch tutorial
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Filed Under: Deep Learning, how-to, Image Classification, Machine Learning, PyTorch, Tutorial

Faster R-CNN Object Detection with PyTorch

Shangeth Rajaa
Satya Mallick
June 18, 2019 Leave a Comment
Computer Vision Stories Courses Deep Learning Feature Detection Machine Learning Object Detection OpenCV 3 Pose PyTorch Segmentation Tracking Tutorial Uncategorized

June 18, 2019 By Leave a Comment

In this post, we will cover Faster R-CNN object detection with PyTorch. We will learn the evolution of object detection from R-CNN to Fast R-CNN to Faster R-CNN. This post is part of our PyTorch for ...

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Tags: artificial intelligence Computer Vision deep learning Object Detection Python PyTorch
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Filed Under: Computer Vision Stories, Courses, Deep Learning, Feature Detection, Machine Learning, Object Detection, OpenCV 3, Pose, PyTorch, Segmentation, Tracking, Tutorial, Uncategorized

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About

I am an entrepreneur with a love for Computer Vision and Machine Learning with a dozen years of experience (and a Ph.D.) in the field.

In 2007, right after finishing my Ph.D., I co-founded TAAZ Inc. with my advisor Dr. David Kriegman and Kevin Barnes. The scalability, and robustness of our computer vision and machine learning algorithms have been put to rigorous test by more than 100M users who have tried our products. Read More…

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