Results 71 to 80 of about 5,384,791 (287)

On‐Chip Photonic Neural Network Architectures

Advanced Optical Materials, EarlyView.
This review presents a comprehensive overview of on‐chip photonic neural network architectures, covering key photonic building blocks, representative network types, and emerging applications. Recent advances, implementation challenges, and future directions are examined, highlighting the potential of integrated photonics to enable ultrafast, energy ...
Seokjin Hong, Berkay Neseli, Seungyeon Cho, Seungsoo Lee, Yeonjun Kim, Seungyoon Choi, Hyo‐Hoon Park, Hamza Kurt   +7 more
wiley   +1 more source

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

A spatial-frequency domain joint detection method of adversarial examples for signal modulation recognition network

Cybersecurity
With the rapid advancement of deep neural networks in wireless communications, applications such as signal modulation recognition and target detection face threats from adversarial example attacks. To enhance system robustness against adversarial attacks,
Wenlin Liu, Linyuan Wang, Nuolin Sun, Dongyang Li, Bin Yan, Houqiang Li   +5 more
doaj   +1 more source

An Adversarial Attack Method against Specified Objects Based on Instance Segmentation

Information, 2022
The deep model is widely used and has been demonstrated to have more hidden security risks. An adversarial attack can bypass the traditional means of defense.
Dapeng Lang, Deyun Chen, Sizhao Li, Yongjun He   +3 more
doaj   +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

Effective and Robust Boundary-Based Outlier Detection Using Generative Adversarial Networks

, 2022
Outlier detection aims to identify samples that do not match the expected patterns or major distribution of the dataset. It has played an important role in many domains such as credit card fraud identification, network intrusion detection, medical image ...
Liang Chang, Liang, Qiliang, Hongzhou Li, Zhang, Ji, Mohamed Jaward Bah, Qiliang Liang, Bah, Mohamed Jaward, Li, Hongzhou, Chang, Liang, Kiran, Rage Uday, Ji Zhang, Rage Uday Kiran   +11 more
core   +1 more source

Transferable Adversarial Example Generation Algorithm for Object Detection [PDF]

Jisuanji gongcheng
The study of adversarial examples can promote innovation in defense methods, identify gaps, and thus improve the robustness of a model. Most of the existing studies on object detection against attack methods suffer from poor black-box migration ability ...
XIANG Haiyun, ZHOU Yao, CHEN Xi
doaj   +1 more source

A State‐Adaptive Koopman Control Framework for Real‐Time Deformable Tool Manipulation in Robotic Environmental Swabbing

Advanced Robotics Research, EarlyView.
This work presents a state‐adaptive Koopman linear quadratic regulator framework for real‐time manipulation of a deformable swab tool in robotic environmental sampling. By combining Koopman linearization, tactile sensing, and centroid‐based force regulation, the system maintains stable contact forces and high coverage across flat and inclined surfaces.
Siavash Mahmoudi, Amirreza Davar, Dongyi Wang   +2 more
wiley   +1 more source

Enhancing Adversarial Example Detection via Feature Attention and High-Frequency Information

IEEE Access
Adversarial examples pose a serious danger to the reliability and security of deep neural networks (DNNs) by inducing incorrect predictions. Existing detection-based methods can identify adversarial inputs to some extent.
Chenxia Chang, Yunfei Lu, Shaowen Yao
doaj   +1 more source

Intelligent Maintenance Review for Robots: Multimodal Information, Deep Diagnosis and Embodied Artificial Intelligence

Advanced Robotics Research, EarlyView.
This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao, Hongbo Wang, Naipeng Li, Shuo Wang, Yaguo Lei, Tonghai Wu, Junyi Cao   +6 more
wiley   +1 more source