no code implementations • 16 Apr 2024 • Hao Feng, Yuanzhe Jia, Ruijia Xu, Mukesh Prasad, Ali Anaissi, Ali Braytee
Image recognition techniques heavily rely on abundant labeled data, particularly in medical contexts.
no code implementations • 8 Dec 2023 • Ali Anaissi, Yuanzhe Jia, Ali Braytee, Mohamad Naji, Widad Alyassine
Comparative evaluations against baseline models including the deep convolutional GAN (DCGAN) and ContraD GAN demonstrate the evident superiority of our proposed model, Damage GAN, in terms of generated image distribution, model stability, and image quality when applied to imbalanced datasets.
no code implementations • 1 Jan 2023 • Kunal Chaturvedi, Ali Braytee, Jun Li, Mukesh Prasad
This paper proposes a novel self-supervised based Cut-and-Paste GAN to perform foreground object segmentation and generate realistic composite images without manual annotations.
no code implementations • 13 Jan 2022 • Yuchong Yao, Xiaohui Wangr, Yuanbang Ma, Han Fang, Jiaying Wei, Liyuan Chen, Ali Anaissi, Ali Braytee
The two recent methods, Balancing GAN (BAGAN) and improved BAGAN (BAGAN-GP), are proposed as an augmentation tool to handle this problem and restore the balance to the data.
no code implementations • 25 Feb 2021 • Ali Braytee, Wei Liu
We show that the learned projection matrix identifies a subset of discriminative features across multiple semantic labels.