Abstract— Content-Based Image Retrieval (CBIR) systems require image classification. This paper presents an application of neural networks (NN) to image ...
Oct 17, 2019 · A new NN architecture which connects a convolutional NN (CNN) with a shallow NN is proposed in order to improve the classification results. This ...
ABSTRACT. Content-Based Image Retrieval (CBIR) systems require image clas- sification. This paper presents an application of neural networks.
A new NN architecture which connects a convolutional NN (CNN) with a shallow NN is proposed in order to improve the classification results. This amelioration is ...
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Jul 11, 2024 · In this network, two architectures are followed. The blocks are designed using inception architecture, and each inception module is created with ...
The proposed multi-fused CNN model demonstrates superior performance, achieving an impressive accuracy rate of 99.32% and 97.15% in classifying fruit types.
Jun 9, 2022 · In reaction to this problem, this paper proposes a general image fusion framework based on an improved convolutional neural network. Firstly, ...
Merging of redundant data can help improve imprecision; and fusion of complementary data can create a more consistent recognition of land cover patterns, in ...
Jun 5, 2024 · Our review explores the comparative analysis between Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs) in the domain of image classification.