Results 101 to 110 of about 221,929 (334)

Information Transmission Strategies for Self‐Organized Robotic Aggregation

Advanced Robotics Research, EarlyView.
In this review, we discuss how information transmission influences the neighbor‐based self‐organized aggregation of swarm robots. We focus specifically on local interactions regarding information transfer and categorize previous studies based on the functions of the information exchanged.
Shu Leng, Zihan Li, Yifeng Shao, Jinhao Liu, Li Yu, Shuguang Li   +5 more
wiley   +1 more source

Generative Adversarial Networks and Its Applications in Biomedical Informatics

Frontiers in Public Health, 2020
The basic Generative Adversarial Networks (GAN) model is composed of the input vector, generator, and discriminator. Among them, the generator and discriminator are implicit function expressions, usually implemented by deep neural networks. GAN can learn
Lan Lan, Lei You, Zeyang Zhang, Zhiwei Fan, Weiling Zhao, Nianyin Zeng, Yidong Chen, Xiaobo Zhou   +7 more
doaj   +1 more source

Multi‐style Chinese art painting generation of flowers

IET Image Processing, 2021
With the proposal and development of Generative Adversarial Networks, the great achievements in the field of image generation are made. Meanwhile, many works related to the generation of painting art have also been derived. However, due to the difficulty
Feifei Fu, Jiancheng Lv, Chenwei Tang, Mao Li   +3 more
doaj   +1 more source

Non-contrast CT synthesis using patch-based cycle-consistent generative adversarial network (Cycle-GAN) for radiomics and deep learning in the era of COVID-19 [PDF]

, 2023
Reza Kalantar, Sumeet Hindocha, Benjamin M. Hunter, Bhupinder Sharma, Nasir Khan, Dow‐Mu Koh, Merina Ahmed, Eric O. Aboagye, Richard W. Lee, Matthew Blackledge   +9 more
openalex   +1 more source

Continual Learning for Multimodal Data Fusion of a Soft Gripper

Advanced Robotics Research, EarlyView.
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley   +1 more source

Training Generative Adversarial Networks With Weights [PDF]

2019 27th European Signal Processing Conference (EUSIPCO), 2019
The impressive success of Generative Adversarial Networks (GANs) is often overshadowed by the difficulties in their training. Despite the continuous efforts and improvements, there are still open issues regarding their convergence properties. In this paper, we propose a simple training variation where suitable weights are defined and assist the ...
Pantazis, Yannis, Paul, Dipjyoti, Fasoulakis, Michail, Stylianou, Yannis   +3 more
openaire   +2 more sources

Robust Physics‐Informed Neural Network Approach for Estimating Heterogeneous Elastic Properties from Noisy Displacement Data

Advanced Science, EarlyView.
Heterogeneous distributions of elasticity parameters are learned from noisy displacement data using the Inverse Elasticity Physics‐Informed Neural Network (IE‐PINN). This approach integrates both data‐driven and physics‐driven methods to address the significant limitations faced by existing techniques.
Tatthapong Srikitrungruang, Sina Aghaee Dabaghan Fard, Matthew Lemon, Jaesung Lee, Yuxiao Zhou   +4 more
wiley   +1 more source

Generative Adversarial Networks: Recent Developments [PDF]

, 2019
10 ...
Zamorski, Maciej, Zdobylak, Adrian, Zięba, Maciej, Świątek, Jerzy   +3 more
openaire   +2 more sources

High‐Asymmetry Metasurface: A New Solution for Terahertz Resonance via Active Learning‐Augmented Diffusion Model

Advanced Science, EarlyView.
A prior knowledge‐guided diffusion model augmented by physics‐constrained active learning is developed to design high‐asymmetry terahertz metamaterials. Trained on only a small set of classical structures, the model efficiently generates new high‐metrics designs.
Qiqi Dai, Yinpeng Wang, Cheng Xu, Dongxiao Li, Prakash Pitchappa, Thomas Caiwei Tan, Ranjan Singh, Chengkuo Lee   +7 more
wiley   +1 more source

Multiscale Design of Dental Restorative Materials: Mechanistic Foundations, Technological Innovations, and Clinical Translation

Advanced Science, EarlyView.
From conventional ceramics to bioinspired smart composites, this review charts the evolution of dental restorative biomaterials. Integrating materials innovation, advanced manufacturing technologies, and bioinspired strategies, it presents a roadmap for developing functional, clinically translatable restorations that combine durability, adaptability ...
Bailei Li, Ruixue Ai, Xinjiani Chen, Yaning Wang, Chenlei Pan, Suxian Song, Chenjie Yang, Yu Zhou, Zhen Zhang, Xiaojun Liu, Xiaodi Liu, Liping Yao, Quanbao Zhang, Wenxue Gu, Rongqing Zhang   +14 more
wiley   +1 more source