Tag Archives | convolutional neural network

Raspberry Pi: Deep learning object detection with OpenCV

A few weeks ago I demonstrated how to perform real-time object detection using deep learning and OpenCV on a standard laptop/desktop. After the post was published I received a number of emails from PyImageSearch readers who were curious if the Raspberry Pi could also be used for real-time object detection. The short answer is “kind […]

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Real-time object detection with deep learning and OpenCV

Today’s blog post was inspired by PyImageSearch reader, Emmanuel. Emmanuel emailed me after last week’s tutorial on object detection with deep learning + OpenCV and asked: “Hi Adrian, I really enjoyed last week’s blog post on object detection with deep learning and OpenCV, thanks for putting it together and for making deep learning with OpenCV […]

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Deep Learning with OpenCV

Two weeks ago OpenCV 3.3 was officially released, bringing with it a highly improved deep learning ( dnn ) module. This module now supports a number of deep learning frameworks, including Caffe, TensorFlow, and Torch/PyTorch. Furthermore, this API for using pre-trained deep learning models is compatible with both the C++ API and the Python bindings, making it […]

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ImageNet classification with Python and Keras

Normally, I only publish blog posts on Monday, but I’m so excited about this one that it couldn’t wait and I decided to hit the publish button early. You see, just a few days ago, François Chollet pushed three Keras models (VGG16, VGG19, and ResNet50) online — these networks are pre-trained on the ImageNet dataset, meaning that they can recognize 1,000 […]

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LeNet – Convolutional Neural Network in Python

In today’s blog post, we are going to implement our first Convolutional Neural Network (CNN) — LeNet — using Python and the Keras deep learning package. The LeNet architecture was first introduced by LeCun et al. in their 1998 paper, Gradient-Based Learning Applied to Document Recognition. As the name of the paper suggests, the authors’ implementation of LeNet was used […]

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