Search: generative adversarial network (GAN) — Academic Articles

Research on Dispersion Compensation of FD-OCT System via Pix2Pix GAN Technique

Eddy Wijanto, Hsu-Chih Cheng, Bo-Hong Liao, Chun-Ming Huang et al. • IEEE Access (2024)

Dispersion in optical coherence tomography (OCT) poses a challenge that is exacerbated by the increased spectral bandwidth, which leads to image blur and feature loss. In this paper, we present a straightforward and cost-effective approach ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3368051

View Article » Original Source ↗

An Improved Dense CNN Architecture for Deepfake Image Detection

Yogesh Patel, Sudeep Tanwar, Pronaya Bhattacharya, Rajesh Gupta et al. • IEEE Access (2023)

Recent advancements in computer vision processing need potent tools to create realistic deepfakes. A generative adversarial network (GAN) can fake the captured media streams, such as images, audio, and video, and make them visually fit othe...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2023.3251417

View Article » Original Source ↗

Wasserstein Generative Adversarial Network Based De-Blurring Using Perceptual Similarity

Minsoo Hong, Yoonsik Choe • Applied Sciences (2019)

The de-blurring of blurred images is one of the most important image processing methods and it can be used for the preprocessing step in many multimedia and computer vision applications. Recently, de-blurring methods have been performed by ...

DOAJ Open Access (DOAJ) DOI: 10.3390/app9112358

View Article » Original Source ↗

A State-of-the-Art Survey on Deep Learning Theory and Architectures

Md Zahangir Alom, Tarek M. Taha, Chris Yakopcic, Stefan K.E. Westberg et al. • Electronics (2019)

In recent years, deep learning has garnered tremendous success in a variety of application domains. This new field of machine learning has been growing rapidly and has been applied to most traditional application domains, as well as some ne...

OPENALEX cc-by DOI: https://doi.org/10.3390/electronics8030292

View Article » Original Source ↗

Composition Design and Property Prediction for AlCoCrCuFeNi High-Entropy Alloy Based on Machine Learning

Cuixia Liu, Meng Meng, Xian Luo • Metals (2025)

Based on the innovative mode driven by “data + artificial intelligence”, in this study, three methods, namely Gaussian noise (GAUSS Noise), the Generative Adversarial Network (GAN), and the optimized Generative Adversarial Network (GANPro),...

DOAJ Open Access (DOAJ) DOI: 10.3390/met15070733

View Article » Original Source ↗

Academic Articles & Research Papers

Research on Dispersion Compensation of FD-OCT System via Pix2Pix GAN Technique

An Improved Dense CNN Architecture for Deepfake Image Detection

Wasserstein Generative Adversarial Network Based De-Blurring Using Perceptual Similarity

A State-of-the-Art Survey on Deep Learning Theory and Architectures

Composition Design and Property Prediction for AlCoCrCuFeNi High-Entropy Alloy Based on Machine Learning