scholarly journals Content-Based Image Retrieval of Chest CT with Convolutional Neural Network for Diffuse Interstitial Lung Disease: Performance Assessment in Three Major Idiopathic Interstitial Pneumonias

2021 ◽  
Vol 22 (2) ◽  
pp. 281
Author(s):  
Hye Jeon Hwang ◽  
Joon Beom Seo ◽  
Sang Min Lee ◽  
Eun Young Kim ◽  
Beomhee Park ◽  
...  
Keyword(s):  
Neural Network ◽  
Interstitial Lung Disease ◽  
Image Retrieval ◽  
Convolutional Neural Network ◽  
Lung Disease ◽  
Performance Assessment ◽  
Chest Ct ◽  
Content Based Image Retrieval ◽  
Idiopathic Interstitial Pneumonias

scholarly journals A Novel Multi Hidden Layer Convolutional Neural Network for Content Based Image Retrieval

2020 ◽  
Vol 9 (3) ◽  
pp. 365-370
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Image Retrieval ◽  
Convolutional Neural Network ◽  
Network Architecture ◽  
Learning Algorithm ◽  
Machine Learning Algorithms ◽  
Content Based Image Retrieval ◽  
Neural Network Architecture ◽  
Query Image

The applications of a content-based image retrieval system in fields such as multimedia, security, medicine, and entertainment, have been implemented on a huge real-time database by using a convolutional neural network architecture. In general, thus far, content-based image retrieval systems have been implemented with machine learning algorithms. A machine learning algorithm is applicable to a limited database because of the few feature extraction hidden layers between the input and the output layers. The proposed convolutional neural network architecture was successfully implemented using 128 convolutional layers, pooling layers, rectifier linear unit (ReLu), and fully connected layers. A convolutional neural network architecture yields better results of its ability to extract features from an image. The Euclidean distance metric is used for calculating the similarity between the query image and the database images. It is implemented using the COREL database. The proposed system is successfully evaluated using precision, recall, and F-score. The performance of the proposed method is evaluated using the precision and recall.

Convolutional neural network (CNN) for interstitial lung disease (ILD) patterns recognition

2019 ◽  
Author(s):  
Lorenzo Aliboni ◽  
Francesca Pennati ◽  
Olivia Dias ◽  
Bruno Baldi ◽  
Marcio Sawamura ◽  
...  
Keyword(s):  
Neural Network ◽  
Interstitial Lung Disease ◽  
Convolutional Neural Network ◽  
Lung Disease

Deep learning for fast bronze inscription image retrieval

2020 ◽  
Vol 4 (4) ◽  
pp. 291-296
Author(s):  
Ziyang Wang ◽  
Wei Zheng ◽  
Youguang Chen
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Image Retrieval ◽  
Convolutional Neural Network ◽  
Local Features ◽  
Content Based Image Retrieval ◽  
Query Image ◽  
Euclidean Metric

Collections of bronze inscription images are increasing rapidly. To use these images efficiently, we proposed an effective content-based image retrieval framework using deep learning. Specifically, we extract discriminative local features for image retrieval using the activations of the convolutional neural network and binarize the extracted features for improving the efficiency of image retrieval, firstly. Then, we use the cosine metric and Euclidean metric to calculate the similarity between the query image and dataset images. The result shows that the proposed framework has an impressive accuracy.

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