2023
DOI: 10.1155/2023/7371907
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Image Classification Based on Light Convolutional Neural Network Using Pulse Couple Neural Network

Abstract: Recently, most image classification studies solicit the intervention of convolutional neural networks because these DL-based classification methods generally outperform other methodologies with higher accuracy. However, this type of deep learning networks require many parameters and have a complex structure with multiple convolutional and pooling layers depending on the objective. These layers compute a large volume of data and it may impact the processing time and the performance. Therefore, this paper propos… Show more

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Cited by 6 publications
(5 citation statements)
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“…For a gray-level image ( x , y ), let R i be ith segmented region, A i be the area of R i (that is the number of pixels contained in region R i ) and C be the normalization factor, then the gray-level uniformity measure of f ( x , y ) [ 24 ] is defined as in Eq. (8).…”
Section: Discussionmentioning
confidence: 99%
See 2 more Smart Citations
“…For a gray-level image ( x , y ), let R i be ith segmented region, A i be the area of R i (that is the number of pixels contained in region R i ) and C be the normalization factor, then the gray-level uniformity measure of f ( x , y ) [ 24 ] is defined as in Eq. (8).…”
Section: Discussionmentioning
confidence: 99%
“…In a gray-level image f ( x , y ) consisting of the object with the average graylevel f O and the background with the average gray-level f b [ 24 ], a gray-level contrast measure can be calculated using Eq. ( 9 ).…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…In this layer, each neuron is connected to all neurons in the respective previous layer, this is referred to as the Fully Connected (FC) approach. It is used as a CNN classifier [29]. This layer follows the basic method of a conventional multi-layer perceptron neural network, as it is a type of Artificial Neural Network (ANN) so it is feed-forward in nature.…”
Section: -5-2 Fully Connectedmentioning
confidence: 99%
“…ResNet constitute a convolutional network that has undergone training on a dataset exceeding 1 million images sourced from the ImageNet database [27] and ResNet-101 model boasts a pre-trained neural network capable of classifying images across 1,700 object categories, making it proficient in learning diverse and effective feature representations for various images. Our research brings notable contributions to the field, particularly in devising a novel CNN model tailored for the classification of diseases in tomato plants.…”
Section: Introductionmentioning
confidence: 99%