Fully Convolutional Siamese Autoencoder for Change Detection in UAV Aerial Imagesdoi:10.1109/lgrs.2019.2945906Daniel B. MesquitaRonaldo F. dos SantosDouglas G. MacharetMario F. M. CamposErickson R. NascimentoIEEE
This is an official implementation of Auto-AD in our TGRS 2021 paper " Auto-AD: Autonomous hyperspectral anomaly detection network based on fully convolutional autoencoder ". - RSIDEA-WHU2020/Auto-AD
(default parameter for masked language models) of the tokens to create a self-supervised training task. In this training task, polyBERT is taught to predict the masked tokens using the non-masked surrounding tokens by adjusting the weights of the Transformer encoders (fill-in-the-blanks task)...
Super-Selfish: Self-Supervised Learning onImages with PyTorch 一个自监督学习的开源库,集成了13个自监督学习算法如Jigsaw Puzzle, ExemplarNet, many autoEncoders, and latest contrastive learning methods。
Video Anomaly Detection and Localization via Gaussian Mixture Fully Convolutional Variational Autoencoderdoi:10.1016/J.CVIU.2020.102920Yaxiang FanGongjian WenDeren LiShaohua QiuMartin D. LevineFei XiaoAcademic Press
In this paper, we present a novel unsupervised multiscale feature-clustering-based fully convolutional autoencoder (MS-FCAE) method that efficiently and accurately inspects various types of texture defects based on a small number of defect-free texture samples. The proposed MS-FCAE method utilizes...
In this paper, a hybrid attention-based encoder–decoder fully convolutional network (HA-EDNet) is presented for PolSAR classification. Unlike traditional CNN-based approaches, the encoder–decoder fully convolutional network (EDNet) can use an arbitrary-size image as input without dividing. Then, ...
The proposed algorithm is based on both an autoencoder (AE) and a fully convolutional neural network (FCN). The AE is adopted for the self-generation of templates from test targets for defect detection. Because the templates are produced from the test targets, the position alignment issues for...