A survey on generative adversarial networks for imbalance problems in computer vision tasks

V Sampath, I Maurtua, JJ Aguilar Martin, A Gutierrez - Journal of big Data, 2021‏ - Springer
Any computer vision application development starts off by acquiring images and data, then
preprocessing and pattern recognition steps to perform a task. When the acquired images …

A survey on gans for anomaly detection

F Di Mattia, P Galeone, M De Simoni… - arxiv preprint arxiv …, 2019‏ - arxiv.org
Anomaly detection is a significant problem faced in several research areas. Detecting and
correctly classifying something unseen as anomalous is a challenging problem that has …

QCD or What?

T Heimel, G Kasieczka, T Plehn, J Thompson - SciPost Physics, 2019‏ - scipost.org
Autoencoder networks, trained only on QCD jets, can be used to search for anomalies in jet-
substructure. We show how, based either on images or on 4-vectors, they identify jets from …

Virtual microstructure design for steels using generative adversarial networks

JW Lee, NH Goo, WB Park, M Pyo… - Engineering …, 2021‏ - Wiley Online Library
The prediction of macro‐scale materials properties from microstructures, and vice versa,
should be a key part in modeling quantitative microstructure‐physical property relationships …

Semi-supervised learning using adversarial training with good and bad samples

W Li, Z Wang, Y Yue, J Li, W Speier, M Zhou… - Machine Vision and …, 2020‏ - Springer
In this work, we investigate semi-supervised learning (SSL) for image classification using
adversarial training. Previous results have illustrated that generative adversarial networks …

Cross attention transformers for multi-modal unsupervised whole-body pet anomaly detection

A Patel, PD Tudosiu, WHL Pinaya, G Cook… - MICCAI Workshop on …, 2022‏ - Springer
Cancers can have highly heterogeneous uptake patterns best visualised in positron
emission tomography. These patterns are essential to detect, diagnose, stage and predict …

Anomaly detection of aerospace facilities using GANomaly

J Du, L Guo, L Song, H Liang, T Chen - Proceedings of the 2020 5th …, 2020‏ - dl.acm.org
In the field of aerospace, the abnormal detection of data is of great significance. The rapid
and effective detection of abnormal parameters is key to find potential failures of spacecraft …

Image generation using generative adversarial networks

O Metri, HR Mamatha - Generative Adversarial Networks for Image-to …, 2021‏ - Elsevier
Ever heard of generation of image datasets, human faces, cartoon characters, 3D objects,
image-to-image and text-to-image translation, face aging, photo blending, and others? How …

A generative model based approach for zero-shot breast cancer segmentation explaining pixels' contribution to the model's prediction

P Mukherjee, M Pal, L Ghosh, A Konar - Interpretable Artificial Intelligence …, 2021‏ - Springer
Deep learning has extensively helped us to analyze complicated distributions of data and
extract meaningful information from the same. But the fundamental problem still remains …

Segmentation Explaining Pixels'

P Mukherjee, M Pal, L Ghosh… - … Artificial Intelligence: A …, 2021‏ - books.google.com
Deep learning has extensively helped us to analyze complicated distributions of data and
extract meaningful information from the same. But the fundamental problem still remains …