Results 11 to 20 of about 11,738,094 (251)
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
doaj +2 more sources
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
doaj +2 more sources
CISA: Context Substitution for Image Semantics Augmentation
Mathematics, 2023 Large datasets catalyze the rapid expansion of deep learning and computer vision. At the same time, in many domains, there is a lack of training data, which may become an obstacle for the practical application of deep computer vision models.
Sergey Nesteruk +8 more
doaj +2 more sources
Cooperative Augmentation of Smart Objects with Projector-Camera Systems [PDF]
, 2007 In this paper we present a new approach for cooperation between mobile smart objects and projector-camera systems to enable augmentation of the surface of objects with interactive projected displays.
Molyneaux, David +7 more
core +5 more sources
Image Augmentation Techniques for Mammogram Analysis. [PDF]
J Imaging, 2022 Research in the medical imaging field using deep learning approaches has become progressively contingent. Scientific findings reveal that supervised deep learning methods’ performance heavily depends on training set size, which expert radiologists must ...
Oza P +4 more
europepmc +2 more sources
The Effect of Data Augmentation in Deep Learning with Drone Object Detection
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2023 Drone object detection is one of the main applications of image processing technology and pattern recognition using deep learning. However, the limited drone image data that can be accessed for training detection algorithms is a challenge in the ...
Ariel Yonatan Alin +2 more
doaj +1 more source
A Deep Learning Image Data Augmentation Method for Single Tumor Segmentation
Frontiers in Oncology, 2022 PurposeMedical imaging examination is the primary method of diagnosis, treatment, and prevention of cancer. However, the amount of medical image data is often not enough to meet deep learning needs. This article aims to expand the small data set in tumor
Chunling Zhang +6 more
doaj +1 more source
Image augmentation methods within IAB.
, 2022 Image augmentation methods within IAB.
Fan Wang (135182) +5 more
core +1 more source
Scientific Reports, 2022 Artificial intelligence (AI) applications in medical imaging continue facing the difficulty in collecting and using large datasets. One method proposed for solving this problem is data augmentation using fictitious images generated by generative ...
Ryo Toda +5 more
doaj +1 more source
Local Augment: Utilizing Local Bias Property of Convolutional Neural Networks for Data Augmentation
IEEE Access, 2021 Data augmentation is an effective way to increase the diversity of existing training datasets that result in improved generalization ability of convolutional neural networks (CNNs). The augmentation effect is usually global for the existing methods i.e.,
Youmin Kim +2 more
doaj +1 more source