-
3D MRI brain tumor segmentation using autoencoder regularization
Automated segmentation of 3D brain tumors from 3D magnetic resonance images (MRIs) is necessary for the diagnosis, monitoring, and treatment planning of the disease. -
End-to-End Latent Fingerprint Search
Latent fingerprints are one of the most important and widely used sources of evidence in law enforcement and forensic agencies. The proposed end-to-end latent search system is... -
Autoencoder-Based Regression Dataset
The dataset used in this paper is a sampled dataset for autoencoder-based regression models. -
LiveJournal
Matrix factorization (MF) and Autoencoder (AE) are among the most successful approaches of unsupervised learning. -
Koopcon: A new approach towards smarter and less complex learning
The dataset condensation problem involves transforming a large-scale training set X into a smaller synthetic set X'. -
Testing Data set
The dataset used for testing the autoencoder-based false data injection attack detector. -
Training Data set
The dataset used for training the autoencoder-based false data injection attack detector. -
IEEE 118-bus system
The IEEE 118-bus system dataset is used to test the proposed reinforcement learning-based mitigation strategy for Multi-Stage Cascading Failure problem. -
XPCS Denoising Dataset (Test)
The dataset used for testing the denoising autoencoder model for noise reduction in XPCS data. -
XPCS Denoising Dataset
The dataset used for training a denoising autoencoder model for noise reduction in X-ray Photon Correlation Spectroscopy (XPCS) data. -
Asymmetrical autoencoder with a sparsifying DCST layer for gearbox sensor dat...
The proposed asymmetrical autoencoder-type neural network for gearbox sensor data compression. -
Using Decision Tree as Local Interpretable Model in Autoencoder-based LIME
The paper introduces a new version of ALIME, which uses a decision tree instead of a linear model as the locally interpretable model. -
Autoencoder& GANs for Imbalanced Multi-Omics
The proposed model is applied to two publicly available datasets, the first is the Cancer Genome Atlas (TCGA) Breast Invasive Carcinoma (BRCA) dataset, which contains DNA... -
Simplex Autoencoders
Synthetic data generation is increasingly important due to privacy concerns. While Autoencoder-based approaches have been widely used for this purpose, sampling from their... -
LatentGAN Autoencoder: Learning Disentangled Latent Distribution
LatentGAN Autoencoder: Learning Disentangled Latent Distribution -
Learning Not to Reconstruct Anomalies
Video anomaly detection is often seen as one-class classification (OCC) problem due to the limited availability of anomaly examples. -
OpenNDD: Open Set Recognition for Neurodevelopmental Disorders Detection
Open set recognition framework for ASD-aided diagnosis -
Video Anomaly Detection by Estimating Likelihood of Representations
Video anomaly detection is a challenging task not only because it involves solving many sub-tasks such as motion representation, object localization and action recognition, but...
