http://www.bing.com:80/search?q=Auto+Encoder+Semi-SupervisedSearch resultshttp://www.bing.com:80/s/a/rsslogo.gifhttp://www.bing.com:80/search?q=Auto+Encoder+Semi-SupervisedCopyright © 2026 Microsoft. All rights reserved. These XML results may not be used, reproduced or transmitted in any manner or for any purpose other than rendering Bing results within an RSS aggregator for your personal, non-commercial use. Any other use of these results requires express written permission from Microsoft Corporation. By accessing this web page or using these results in any manner whatsoever, you agree to be bound by the foregoing restrictions.https://www.researchgate.net/publication/386353451_Regularized_Masked_Auto-Encoder_for_Semi-Supervised_Hyperspectral_Image_ClassificationRequest PDF | Regularized Masked Auto-Encoder for Semi-Supervised Hyperspectral Image Classification | As the most prevalent self-supervised representation learning (SSRL) model, the masked auto ...Tue, 31 Dec 2024 07:09:00 GMThttps://link.springer.com/chapter/10.1007/978-3-319-46672-9_10We propose to learn the autoencoder for a semi-supervised paradigm, i.e. with both labeled and unlabeled samples available. Given labeled and unlabeled data, our proposed autoencoder automatically adjusts – for unlabeled data it acts as a standard autoencoder (unsupervised) and for labeled data it additionally learns a linear classifier.Mon, 30 Mar 2026 05:42:00 GMThttps://towardsdatascience.com/semi-supervised-anomaly-detection-using-auto-encoders-b1b0a5d8aa56/A convolutional auto encoder based approach for semi-supervised anomaly detection in images.Thu, 02 Apr 2026 12:26:00 GMThttps://www.sciencedirect.com/science/article/pii/S1568494624001078Auto-encoder (AE) network, a deep learning method, is widely researched in process monitoring for its highly derivable. Lee et al. [21] proposed a variational auto-encoder (VAE) as a monitoring method to address both nonlinear and nonnormal situations in high-dimensional processes.Sat, 04 Apr 2026 13:07:00 GMThttps://ar5iv.labs.arxiv.org/html/2210.09486Abstract We present a new semi-supervised domain adaptation framework that combines a novel auto-encoder-based domain adaptation model with a simultaneous learning scheme providing stable improvements over state-of-the-art domain adaptation models.Wed, 11 Mar 2026 18:50:00 GMThttps://www.researchgate.net/publication/355288188_Semi-Supervised_Auto-Encoder_Graph_Network_for_Diabetic_Retinopathy_GradingWe propose a Semi-supervised Auto-encoder Graph Network (SAGN) for the challenging DR diagnosis to relax this constraint.Fri, 27 Oct 2023 06:01:00 GMThttps://pubmed.ncbi.nlm.nih.gov/30415723/Methods: In this paper, we present a semi-supervised deep learning strategy, the stacked sparse auto-encoder (SSAE) based classification, for cancer prediction using RNA-seq data. The proposed SSAE based method employs the greedy layer-wise pre-training and a sparsity penalty term to help capture and extract important information from the high-dimensional data and then classify the samples.Tue, 31 Mar 2026 17:22:00 GMThttps://www.nature.com/articles/s41598-025-00349-zA novel fully convolutional auto-encoder based on dual clustering and latent feature adversarial consistency for hyperspectral anomaly detection. Remote Sens. 16, 717 (2024). Article ADS Google ...Sun, 25 May 2025 23:59:00 GMThttps://www.researchgate.net/publication/330664335_A_semi-supervised_auto-encoder_using_label_and_sparse_regularizations_for_classificationThe semi-supervised auto-encoder (SSAE) is a promising deep-learning method that integrates the advantages of unsupervised and supervised learning processes. The former learning process is ...Thu, 08 Jun 2023 14:03:00 GMThttps://www.researchgate.net/publication/364305756_Semi-Supervised_Domain_Adaptation_with_Auto-Encoder_via_Simultaneous_LearningWe present a new semi-supervised domain adaptation framework that combines a novel auto-encoder-based domain adaptation model with a simultaneous learning scheme providing stable improvements over ...Mon, 25 Dec 2023 17:58:00 GMT