Deep learning in virtual try-on: A comprehensive survey

T Islam, A Miron, X Liu, Y Li - IEEE Access, 2024 - ieeexplore.ieee.org
Virtual try-on technology has gained significant importance in the retail industry due to its
potential to transform the way customers interact with products and make purchase …

Image-based virtual try-on: A survey

D Song, X Zhang, J Zhou, W Nie, R Tong… - International Journal of …, 2024 - Springer
Image-based virtual try-on aims to synthesize a naturally dressed person image with a
clothing image, which revolutionizes online shop** and inspires related topics within …

Double policy estimation for importance sampling in sequence modeling-based reinforcement learning

H Zhou, T Lan, V Aggarwal - NeurIPS 2023 Foundation Models for …, 2023 - openreview.net
Offline reinforcement learning aims to utilize datasets of previously gathered environment-
action interaction records to learn a policy without access to the real environment. Recent …

OAM modes classification and demultiplexing via Fourier optical neural network

J Ye, B Jahannia, H Kang, H Wang… - Complex Light and …, 2024 - spiedigitallibrary.org
Here, we present a free-space optical communication system, adept at managing alignment
deviations and the challenges posed by the atmospheric turbulence in the transmission of …

Orbital angular momentum beams multiplexing and demultiplexing using hybrid optical-electronic neural network

J Ye, H Kang, S Altaleb, H Wang, C Patil… - … From Materials and …, 2024 - spiedigitallibrary.org
Recent advancements in optical communications have explored the use of spatially
structured beams, especially orbital angular momentum (OAM) beams, to achieve high …

Advanced 4f-based free-space optical system

H Kang, J Ye, B Jahannia, S Altaleb… - Complex Light and …, 2024 - spiedigitallibrary.org
Here, we introduce a framework leveraging a free-space optical system based on the 4f
configuration, inspired by the SWIFFT algorithms, designed to significantly enhance the …

Decision-Making via Optimization in Challenging Environment: Bayesian and Multi-Agent Reinforcement Learning Perspectives

Y Mei - 2025 - search.proquest.com
Decision-making is essential in many real-world problems, where the goal is to select
actions that optimize long-term outcomes under uncertainty. From tuning hyperparameters to …

Effective Value Function Factorization and Exploration in Multi-Agent Reinforcement Learning

H Zhou - 2024 - search.proquest.com
The evolution of computer science has profoundly impacted decision-making processes
across diverse domains, culminating in the development of artificial intelligence (AI) and …

Reconfigurable complex convolution module based optical data compression and hashing algorithm

H Kang, J Ye, BM Nouri, B Jahannia… - AI and Optical Data …, 2024 - spiedigitallibrary.org
Here, we explores the forefront of optical dynamic real-time signal processing with the
introduction of a Reconfigurable Complex Convolution Module (RCCM), leveraging …