In this paper, we propose a novel convolution technique of fast algorithms for convolutional neural networks using continuous differential images.
Continuous Differential Image-based Fast Convolution for ... - IEEE Xplore
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The. NVIDIA cuDNN is a library for deep learning acceleration using an NVIDIA GPU and provides various optimization techniques for convolutional operation [5].
This paper proposes a novel convolution technique of fast algorithms for convolutional neural networks using continuous differential images that improves ...
Convolution operation is based on extracting feature maps by sliding the trainable filters on the image and calculating the activation values. These feature ...
Dec 25, 2017 · Abstract: This paper introduces the concept of continuous convolution to neural networks and deep learning applications in general.
The significant features of our algorithm are that the SOE method is efficient and accurate, and works for general kernels with controllable upperbound of ...
This paper proposes a novel convolution technique of fast algorithms for convolutional neural networks using continuous differential images that improves the ...
Convolutional Neural Networks: A Comprehensive Guide - Medium
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Feb 7, 2024 · Convolutional Neural Networks, commonly referred to as CNNs are a specialized type of neural network designed to process and classify images ...
Aug 10, 2024 · In this paper, we propose a novel convolution technique of fast algorithms for convolutional neural networks using continuous differential ...
Fast Convolution Algorithm for Convolutional Neural Networks
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Researchers [11] developed a Faster R-CNN method that improves region proposals to a certain extent, and applied it to image detection and mask recognition and ...
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