Optimizing the performance of convolutional neural network ...

Optimizing the performance of convolutional neural network ... - Nature

This study investigates the optimal configuration of convolutional neural network (CNN)-based MEC by proposing an effective data segmentation technique and a ...

Optimizing the performance of convolutional neural network for ...

Deep neural networks (DNNs) have demonstrated higher performance results when compared to traditional approaches for implementing robust ...

Optimizing Performance of Convolutional Neural Network Using ...

Based on the deep learning algorithms, there are many recent rapid growths of applications. A deep learning algorithm which is expanded from Artificial ...

Improving Performance of Convolutional Neural Network! - Medium

It will give you certain ideas to lift the performance of CNN ... The list is divided into 4 topics ... 1. Tune Parameters ... 2. Image Data ...

How to Optimize CNN Performance During Training - LinkedIn

1 ... Choose the right architecture ... 2 ... Use data augmentation ... 3 ... Apply regularization ... 4 ... Adjust the learning rate ... 5 ... Monitor the ...

Optimizing Convolutional Neural Network Architecture - arXiv

In this paper, we propose Optimizing Convolutional Neural Network Architecture (OCNNA), a novel CNN optimization and construction method based on pruning and ...

Optimization of the convolutional neural network classification model ...

To improve students' ability to recognize and appreciate artworks, and further enhance their academic performance and classroom satisfaction ...

Performance Optimization of Convolutional Neural Networks (CNN ...

The deep learning model will be based on Tensorflow and Keras sequential APIs and will aim to efficiently classify different fruit types and predict fruit type.

Optimizing CPU Performance for Convolutional Neural Networks

We hypothesize and study various systems optimiza- tions to speed up the performance of convolutional neu- ral networks on CPUs. Currently, large-scale CNN ...

Optimizing Convolutional Neural Network Architectures - MDPI

It is a novel CNN optimization and construction method based on pruning designed to establish the importance of convolutional layers.

How to improve the performance of CNN Model for a specific ...

100% accuracy on training data is an indicator that the model has overfitted. It basically means the network memorized the training data but failed to learn ...

Improving Techniques for Convolutional Neural Networks ...

As network depth rises, accuracy saturates and declines quickly [2]. Several approaches proved to improve performance or reduce computational ...

Optimization and acceleration of convolutional neural networks

Some times DWM shows better performance as compared to CuDNN (Huang et al., 2020). (Chao Cheng & Keshab K.Path in 2020) Proposed fast convolution algorithm for ...

Optimising the Performance of Convolutional Neural Networks ...

Figure 2: The primitive selection process when using a neural network based performance model. denotes the number of layers of the CNN. ...

(PDF) Improving Techniques for Convolutional Neural Networks ...

used to improve convolutional neural network performance. Keywords: Accuracy, Convolutional Neural Networks, Impr ...

Optimizing CPU Performance for Convolutional Neural Networks

This work hypothesize and study various systems optimizations to speed up the performance of convolutional neural networks on CPUs by borrowing techniques ...

7 Best Techniques To Improve The Accuracy of CNN W/O Overfitting

Dataset — CIFAR 10 · Data normalization. We normalized the image tensors by subtracting the mean and dividing by the standard deviation of pixels ...

Optimizing performance of feedforward and convolutional neural ...

We propose a novel Adaptive Activation algorithm, AdAct, exhibiting promising performance improvements in diverse CNN and multilayer perceptron configurations.

Optimization of convolutional neural network for glass-forming ability ...

The accuracy of the optimized model is greatly improved. Abstract. The performance of convolutional neural networks (CNN) is largely determined by various ...

How to implement and optimize convolutional neural networks ...

This guide offers a roadmap to effectively design, train, and refine CNNs within TensorFlow, ensuring robust performance on image recognition, classification, ...