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Classifiers Comparison for Convolutional Neural Networks (CNNs) in Image Classification
2019 IEEE/ACM 23rd International Symposium on Distributed Simulation and Real Time Applications (DS-RT), 2019This paper presents a comparison between five different classifiers (Multi-class Logistic Regression (MLR), Support Vector Machine (SVM), k-Nearest Neighbor (kNN), Random Forest (RF) and Gaussian Naive Bayes (GNB)) to be used in a Convolutional Neural Network (CNN) in order to perform images classification.
Mauro Tropea, Giuseppe Fedele
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DL-CNN: Double Layered Convolutional Neural Networks
Proceedings of the 24th International Conference on Enterprise Information Systems, 2022Lixin Fu 0001, Rohith Rangineni
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Convolutional Neural Networks (CNNs) for Medical Imaging
The chapter delves into the transformative impact of Convolutional Neural Networks (CNNs) on medical imaging, highlighting their ability to enhance diagnostic accuracy, streamline workflows, and enable real-time image analysis. It provides a comprehensive overview of CNN architectures, their principles, and their integration into diverse medical ...S. Aishwarya +5 more
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Morph-CNN: A Morphological Convolutional Neural Network for Image Classification
2017Deep neural networks, an emergent type of feed forward networks, have gained a lot of interest especially for computer vision problems such as analyzing and understanding digital images. In this paper, a new deep learning architecture is proposed for image analysis and recognition. Two key ingredients are involved in our architecture.
Dorra Mellouli +3 more
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Review on Convolutional Neural Network (CNN) Applied to Plant Leaf Disease Classification
Agriculture (Switzerland), 2021Jinzhu Lu, Lijuan Tan, Huanyu Jiang
exaly
Convolutional Neural Networks (CNN) for Predictive Analytics
2023Phillip A. Laplante +1 more
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