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Tutorials
In this tutorial, you will learn how to use autoencoders to denoise images using Keras, TensorFlow, and Deep Learning. Today’s tutorial is part two in our three-part series on the applications of autoencoders: Autoencoders with Keras, TensorFlow, and Deep Learning…
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In this tutorial, you will learn how to implement and train autoencoders using Keras, TensorFlow, and Deep Learning. Today’s tutorial kicks off a three-part series on the applications of autoencoders: Autoencoders with Keras, TensorFlow, and Deep Learning (today’s tutorial) Denoising…
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In this tutorial, you’ll learn how to use OpenCV’s “dnn” module with an NVIDIA GPU for up to 1,549% faster object detection (YOLO and SSD) and instance segmentation (Mask R-CNN). Last week, we discovered how to configure and install OpenCV…
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In this tutorial, you will learn how to use OpenCV’s “Deep Neural Network” (DNN) module with NVIDIA GPUs, CUDA, and cuDNN for 211-1549% faster inference. Back in August 2017, I published my first tutorial on using OpenCV’s “deep neural network”…
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In this tutorial, you will learn how to utilize YOLO and Tiny-YOLO for near real-time object detection on the Raspberry Pi with a Movidius NCS. The YOLO object detector is often cited as being one of the fastest deep learning-based…
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In this tutorial, you will learn how to perform anomaly/novelty detection in image datasets using OpenCV, Computer Vision, and the scikit-learn machine learning library. Imagine this — you’re fresh out of college with a degree in Computer Science. You focused…
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In this tutorial you will learn how to use dlib’s find_min_global function to optimize the options and hyperparameters to dlib’s shape predictor, yielding a more accurate model. A few weeks ago I published a two-part series on using dlib to…
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In this tutorial, you will learn two ways to implement label smoothing using Keras, TensorFlow, and Deep Learning. When training your own custom deep neural networks there are two critical questions that you should constantly be asking yourself: Am I…
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In this tutorial, you will learn how to optimally tune dlib’s shape predictor hyperparameters and options to obtain a shape predictor that balances speed, accuracy, and model size. Today is part two in our two-part series on training custom shape…
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Deep Learning