Survey of Image Data Augmentation Techniques Based on Deep Learning [PDF]
Jisuanji kexueIn recent years,deep learning has demonstrated excellent performance in many computer vision tasks such as image classification,object detection,and image segmentation.Deep neural networks usually rely on a large amount of training data to avoid ...
SUN Shukui, FAN Jing, SUN Zhongqing, QU Jinshuai, DAI Tingting
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A framework for in-vivo human brain tumor detection using image augmentation and hybrid features. [PDF]
Health Inf Sci Syst, 2022 Jha M, Gupta R, Saxena R.
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BitMix: data augmentation for image steganalysis [PDF]
Electronics Letters, 2020 Convolutional neural networks for image steganalysis demonstrate better performances with employing concepts from high‐level vision tasks. The major employed concept is to use data augmentation to avoid overfitting due to limited data. To augment data without damaging the message embedding, only rotating multiples of
I.‐J. Yu +3 more
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Observations on K-Image Expansion of Image-Mixing Augmentation
IEEE Access, 2023 Image-mixing augmentations (e.g., Mixup and CutMix), which typically involve mix ing two images, have become the de-facto training techniques for image classification.
Joonhyun Jeong +5 more
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Improved imaging of the augmented breast [PDF]
American Journal of Roentgenology, 1988 The breast containing an augmentation implant presents a challenge to the mammographer and is often considered unsuitable for adequate mammographic evaluation. A modified positioning technique is described. By displacing the implant posteriorly against the chest wall and pulling breast tissue over and in front of the implant, marked improvement in ...
G W, Eklund +3 more
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ROTATION-GAMMA CORRECTION AUGMENTATION ON CNN-DENSE BLOCK FOR SOIL IMAGE CLASSIFICATION
Applied Computer Science, 2023 Soil is a solid-particle that covers the earth's surface. Soils can be classified based their color. The color can be an indication of soil properties and soil conditions. Soil image classification requires high accuracy and caution.
Sri INDRA MAIYANTI +6 more
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Data Augmentation Techniques for Deep Learning-Based Medical Image Analyses
대한영상의학회지, 2020 Medical image analyses have been widely used to differentiate normal and abnormal cases, detect lesions, segment organs, etc. Recently, owing to many breakthroughs in artificial intelligence techniques, medical image analyses based on deep learning ...
Mingyu Kim, Hyun-Jin Bae
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Smart(Sampling)Augment: Optimal and Efficient Data Augmentation for Semantic Segmentation
Algorithms, 2022 Data augmentation methods enrich datasets with augmented data to improve the performance of neural networks. Recently, automated data augmentation methods have emerged, which automatically design augmentation strategies.
Misgana Negassi +2 more
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Analysis and best parameters selection for person recognition based on gait model using CNN algorithm and image augmentation. [PDF]
J Big Data, 2021 Person Recognition based on Gait Model (PRGM) and motion features is are indeed a challenging and novel task due to their usages and to the critical issues of human pose variation, human body occlusion, camera view variation, etc. In this project, a deep
Saleh AM, Hamoud T.
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Effects of data count and image scaling on Deep Learning training [PDF]
PeerJ Computer Science, 2020 Background Deep learning using convolutional neural networks (CNN) has achieved significant results in various fields that use images. Deep learning can automatically extract features from data, and CNN extracts image features by convolution processing ...
Daisuke Hirahara +3 more
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