2 code implementations • 28 Dec 2023 • Wonjoon Chang, Dahee Kwon, Jaesik Choi
Understanding intermediate representations of the concepts learned by deep learning classifiers is indispensable for interpreting general model behaviors.
no code implementations • 22 Sep 2022 • Wonjoon Chang, Dahee Kwon, Bumjin Park
In addition, we propose Edge-oriented Representation Network (EoREN) that can reconstruct the image with clear edges by fitting gradient information (Edge-oriented module).
1 code implementation • 17 Jan 2022 • Hwanil Choi, Wonjoon Chang, Jaesik Choi
Even though Generative Adversarial Networks (GANs) have shown a remarkable ability to generate high-quality images, GANs do not always guarantee the generation of photorealistic images.
no code implementations • 27 Apr 2020 • Sohee Cho, Ginkyeng Lee, Wonjoon Chang, Jaesik Choi
Recently deep neural networks demonstrate competitive performances in classification and regression tasks for many temporal or sequential data.