Ct Gan

Conditional Generative Adversarial Networks (cGANs), and their variations, are increasingly used to generate and manipulate data across diverse fields, aiming to improve data augmentation, anomaly detection, and cross-modal data fusion. Current research focuses on enhancing cGAN architectures, such as incorporating transformers and variational autoencoders, to improve the quality and realism of generated data, particularly in handling imbalanced datasets and capturing complex dependencies. This work has significant implications for various applications, including medical image analysis (e.g., Alzheimer's disease prediction), cybersecurity (anomaly detection in cyber-physical systems), and design optimization under uncertainty.

Papers

November 23, 2023

Automated 3D Tumor Segmentation using Temporal Cubic PatchGAN (TCuP-GAN)
Kameswara Bharadwaj Mantha, Ramanakumar Sankar, Lucy Fortson
Brain Tumor Segmentation 3D Brain Tumor Ct Gan Mitochondrion Segmentation Temporal Gan

November 4, 2023

MTS-DVGAN: Anomaly Detection in Cyber-Physical Systems using a Dual Variational Generative Adversarial Network
Haili Sun, Yan Huang, Lansheng Han, Cai Fu, Hongle Liu, Xiang Long
Generative Model Generative Adversarial Network Anomaly Detection Cyber Physical System Physical World Attack Ct Gan

September 28, 2023

Alzheimer's Disease Prediction via Brain Structural-Functional Deep Fusing Network
Qiankun Zuo, Junren Pan, Shuqiang Wang
Generative Adversarial Network Alzheimer'S Disease Brain Function Disease Prediction Deep Feature Fusion Ct Gan

April 24, 2023

ComGAN: Toward GANs Exploiting Multiple Samples
Haeone Lee
GAN Model Ct Gan

March 16, 2023

Instance-Conditioned GAN Data Augmentation for Representation Learning
Pietro Astolfi, Arantxa Casanova, Jakob Verbeek, Pascal Vincent, Adriana Romero-Soriano, Michal Drozdzal
Generative Model Data Augmentation Representation Learning Based Augmentation Ct Gan

June 28, 2022

Improving Correlation Capture in Generating Imbalanced Data using Differentially Private Conditional GANs
Chang Sun, Johan van Soest, Michel Dumontier
Generative Adversarial Network Imbalanced Data Synthetic Medical Data Correlation Graph Ct Gan Private Generative Adversarial Network

June 20, 2022

Cross-Modal Transformer GAN: A Brain Structure-Function Deep Fusing Framework for Alzheimer's Disease
Junren Pan, Shuqiang Wang
Generative Adversarial Network Alzheimer'S Disease Common Disease Resting State Cross Modal Transformer Deep Feature Fusion Ct Gan

April 22, 2022

SE-GAN: Skeleton Enhanced GAN-based Model for Brush Handwriting Font Generation
Shaozu Yuan, Ruixue Liu, Meng Chen, Baoyang Chen, Zhijie Qiu, Xiaodong He
Full Model Font Generation Skeleton Annotation Handwriting Style Ct Gan Image Translation Model Skeleton Encoder

April 2, 2022

IR-GAN: Image Manipulation with Linguistic Instruction by Increment Reasoning
Zhenhuan Liu, Jincan Deng, Liang Li, Shaofei Cai, Qianqian Xu, Shuhui Wang, Qingming Huang
Image Editing Conditional Image Generation Iterative Reasoning Ct Gan

February 25, 2022

Reconstruction of Perceived Images from fMRI Patterns and Semantic Brain Exploration using Instance-Conditioned GANs
Furkan Ozcelik, Bhavin Choksi, Milad Mozafari, Leila Reddy, Rufin VanRullen
Full State Reconstruction C Gan Visual Object Conditional GAN Semantic Exploration Ct Gan

February 21, 2022

GAN-DUF: Hierarchical Deep Generative Models for Design Under Free-Form Geometric Uncertainty
Wei Wayne Chen, Doksoo Lee, Oluwaseyi Balogun, Wei Chen
Product Design Robust Optimization Generative Adversarial Geometric Optimization Ct Gan Geometric Uncertainty Hierarchical Deep Generative

Ct Gan

Papers

Automated 3D Tumor Segmentation using Temporal Cubic PatchGAN (TCuP-GAN)

MTS-DVGAN: Anomaly Detection in Cyber-Physical Systems using a Dual Variational Generative Adversarial Network

Alzheimer's Disease Prediction via Brain Structural-Functional Deep Fusing Network

ComGAN: Toward GANs Exploiting Multiple Samples

Instance-Conditioned GAN Data Augmentation for Representation Learning

Improving Correlation Capture in Generating Imbalanced Data using Differentially Private Conditional GANs

Cross-Modal Transformer GAN: A Brain Structure-Function Deep Fusing Framework for Alzheimer's Disease

SE-GAN: Skeleton Enhanced GAN-based Model for Brush Handwriting Font Generation

IR-GAN: Image Manipulation with Linguistic Instruction by Increment Reasoning

Reconstruction of Perceived Images from fMRI Patterns and Semantic Brain Exploration using Instance-Conditioned GANs

GAN-DUF: Hierarchical Deep Generative Models for Design Under Free-Form Geometric Uncertainty