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Convolution Operation in CNN Explained!
🚀 What is Convolution in CNN? In this short, get a lightning-fast explanation of the convolution operation in Convolutional Neural Networks (CNNs) — the core building block of how machines understand images! 📌 Understand: - How convolution works - Role of filters/kernels - Feature extraction from images Perfect for students, AI ...
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Visualisation of how Convolutional Neural Network works. A Convolutional Neural Network (CNN) operates by applying filters to input data, extracting features through convolution and pooling layers. These filters systematically scan the input, detecting patterns like edges. The network learns these filters during training, enabling it to recognize complex features in images. By combining convolution and pooling layers, CNNs create feature maps that highlight detected features. This process allows
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Visualisation of how Convolutional Neural Network works. A Convolutional Neural Network (CNN) operates by applying filters to input data, extracting features through convolution and pooling layers. These filters systematically scan the input, detecting patterns like edges. The network learns these filters during training, enabling it to recognize complex features in images. By combining convolution and pooling layers, CNNs create feature maps that highlight detected features. This process allows
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