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Max pooling in CNNs explained for deep learning

In this video, we will understand what is Max Pooling in Convolutional Neural Network and why do we use it. Max Pooling in ...
Nature

Convolutional neural networks for automated annotation of cellular cryo-electron tomograms

Cellular electron cryotomography (CryoET) is the dominant technique for studying the structure of interacting, dynamic complexes in their native cellular environment at nanometer resolution. While ...
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Stride in CNNs: The key tweak that matters

In this video, we will understand what is Stride in Convolutional Neural Network. While performing Convolution operation on ...
Risk

Dilated convolutional neural networks for time series forecasting

We present a method for conditional time series forecasting based on an adaptation of the recent deep convolutional WaveNet architecture. The proposed network contains stacks of dilated convolutions ...
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Mastering Convolutional Neural Networks: A Comprehensive Guide to Computer Vision

In recent years, the field of computer vision has witnessed a remarkable transformation with the introduction of Convolutional Neural Networks (CNNs). These deep learning models have revolutionised ...