Results 151 to 160 of about 546,017 (306)

Programmable Dimensional Lithography with Digital Micromirror Devices for Multifunctional Microarchitectures

Advanced Materials Technologies, EarlyView.
This review explores recent advances in digital micromirror device (DMD)‐based lithography, focusing on its programmable light modulation, multi‐material compatibility, and dimensional patterning strategies. It highlights innovations from optical system design to materials integration and multifunctional applications, positioning DMD lithography as a ...
Yubin Lee, Byungcheon Yoo, Chaeyeong Ryu, Jongwon Oh, Dahye Baek, Jiseok Lee   +5 more
wiley   +1 more source

Printed 2.5D‐Microstructures with Material‐Specific Functionalization for Tunable Biosensing

Advanced Materials Technologies, EarlyView.
The 2.5D‐MiSENSE platform integrates a microstructured biosensor with an in‐line milking pipeline to enable real‐time detection of mastitis biomarkers during active milk flow. The system uses a 2.5D microengineered surface and patterned electrodes to enhance milk–sensor interaction.
Matin Ataei Kachouei, Benjamin Corl, Md. Azahar Ali   +2 more
wiley   +1 more source

A novel image feature based self-supervised learning model for effective quality inspection in additive manufacturing

, 2023
Chun Fai Lui, Ahmed Maged, Min Xie
openalex   +1 more source

Hydrogel‐Based Functional Materials: Classifications, Properties, and Applications

Advanced Materials Technologies, EarlyView.
Conductive hydrogels have emerged as promising materials for smart wearable devices due to their outstanding flexibility, multifunctionality, and biocompatibility. This review systematically summarizes recent progress in their design strategies, focusing on monomer systems and conductive components, and highlights key multifunctional properties such as
Zeyu Zhang, Zao Cheng, Patrizio Raffa
wiley   +1 more source

MalSSL—Self-Supervised Learning for Accurate and Label-Efficient Malware Classification

IEEE Access
Malware classification with supervised learning requires a large dataset, which needs an expensive and time-consuming labeling process. In this paper, we explore the efficacy of self-supervised learning techniques for malware classification.
Setia Juli Irzal Ismail, Hendrawan, Budi Rahardjo, Tutun Juhana, Yasuo Musashi   +4 more
doaj   +1 more source

SCARF: Self-Supervised Contrastive Learning using Random Feature\n Corruption [PDF]

, 2021
Dara Bahri, Heinrich Jiang, Yi Tay, Donald Metzler   +3 more
openalex   +1 more source

Soft Robotic Excretory Care Simulator for Nursing Education: Functional and Perceptual Biomimetics Approach

Advanced Robotics Research, EarlyView.
A soft robotic simulator is developed to replicate the digital removal of feces (DRF), a sensitive yet essential nursing procedure. Integrating soft actuators, sensors, and a realistic rectal model, the simulator balances functional fidelity with perceptual realism. Engineering evaluations and nurse feedback confirm its potential to enhance training in
Shoko Miyagawa, Sota Suzuki, Shizuka Watanabe, Zebing Mao, Young Ah Seong, Toshinori Fujie, Tatsuhiro Horii, Kenjiro Tadakuma, Koichi Suzumori, Hiroyuki Nabae, Shingo Maeda   +10 more
wiley   +1 more source

Self-Supervised Equivariant Regularization Reconciles Multiple Instance Learning: Joint Referable Diabetic Retinopathy Classification and Lesion Segmentation [PDF]

, 2022
Wenhui Zhu, Peijie Qiu, Natasha Leporé, Oana M. Dumitrascu, Yalin Wang   +4 more
openalex   +1 more source

Flexible Sensor‐Based Human–Machine Interfaces with AI Integration for Medical Robotics

Advanced Robotics Research, EarlyView.
This review explores how flexible sensing technology and artificial intelligence (AI) significantly enhance human–machine interfaces in medical robotics. It highlights key sensing mechanisms, AI‐driven advancements, and applications in prosthetics, exoskeletons, and surgical robotics.
Yuxiao Wang, Zhipeng Jiang, Sun Hwa Kwon, Matthew Ibrahim, Alexander Dang, Lin Dong   +5 more
wiley   +1 more source

A W-Shaped Self-Supervised Computational Ghost Imaging Restoration Method for Occluded Targets

Sensors
We developed a novel method based on self-supervised learning to improve the ghost imaging of occluded objects. In particular, we introduced a W-shaped neural network to preprocess the input image and enhance the overall quality and efficiency of the ...
Yu Wang, Xiaoqian Wang, Chao Gao, Zhuo Yu, Hong Wang, Huan Zhao, Zhihai Yao   +6 more
doaj   +1 more source