Results 61 to 70 of about 22,071 (254)

Pattern‐Aware Intelligence Enables Nondestructive, Rapid Quantification of High‐Aspect‐Ratio Silicon Etching

Advanced Science, EarlyView.
Pattern‐dependent etching is converted into a physical prior for intelligent reconstruction of high‐aspect‐ratio silicon structures. Combining YOLO‐Pose feature extraction with a topography network, the framework retrieves depth, sidewall angle, and scallop texture from minimal destructive observations, enabling accurate cross‐scale metrology and near ...
Shuyan He, Lang Chen, Bo Wen, Yufeng Jin, Wei Wang   +4 more
wiley   +1 more source

GAN‐LSTM‐3D: An efficient method for lung tumour 3D reconstruction enhanced by attention‐based LSTM

CAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract Three‐dimensional (3D) image reconstruction of tumours can visualise their structures with precision and high resolution. In this article, GAN‐LSTM‐3D method is proposed for 3D reconstruction of lung cancer tumours from 2D CT images. Our method consists of three phases: lung segmentation, tumour segmentation, and tumour 3D reconstruction. Lung
Lu Hong, Mohammad Hossein Modirrousta, Mohammad Hossein Nasirpour, Mohammadreza Mirshekari Chargari, Fardin Mohammadi, Seyed Vahid Moravvej, Leila Rezvanishad, Mohammadreza Rezvanishad, Ivan Bakhshayeshi, Roohallah Alizadehsani, Imran Razzak, Hamid Alinejad‐Rokny, Saeid Nahavandi   +12 more
wiley   +1 more source

Beyond Conventional: A Review of Phytochemical‐Hydrogel Systems Enhanced by AI and 3D Printing for Chronic Wound Management

Advanced Science, EarlyView.
This review systematically bridges chronic wound pathology with natural phytochemical hydrogel therapeutics. A pathology‐to‐phytochemical mechanistic mapping framework is established, linking specific wound hallmarks to targeted phytochemical interventions.
Yitao Zhou, Xing Liu, Cuiyi Wang, Xiaoxuan Zhao, Pengrun Zhang, Jingjing Gu, Qiuhua Sun, Malcolm Xing, Yeqin Yang   +8 more
wiley   +1 more source

Manipulating and measuring variation in deep neural network (DNN) representations of objects

Cognition
We explore how DNNs can be used to develop a computational understanding of individual differences in high-level visual cognition given their ability to generate rich meaningful object representations informed by their architecture, experience, and training protocols.
Jason Kah-Jun Chow, Thomas Palmeri
openaire   +2 more sources

Enhancing Specific Stiffness of Nano‐Architected Materials Through Generative AI and Active Learning

Advanced Science, EarlyView.
A structure‐centric generative framework searches voxelated design space directly, coupling a variational autoencoder with multi‐objective optimization and active learning to progressively expand the validated design domain. The discovered nano‐architectures, realized as pyrolytic carbon by two‐photon lithography, deliver 18–23% higher stiffness and 26–
Jinwook Yeo, Peter Serles, Donggeun Park, Julia R. Greer, Seunghwa Ryu   +4 more
wiley   +1 more source

A Worm Detection System Based on Deep Learning

IEEE Access, 2020
In today's cyber world, worms pose a great threat to the global network infrastructure. In this paper, we propose a worm detection system based on deep learning.
Hanxun Zhou, Yeshuai Hu, Xinlin Yang, Hong Pan, Wei Guo, Cliff C. Zou   +5 more
doaj   +1 more source

Terahertz Channel Modeling, Estimation and Localization in RIS‐Assisted Systems

Advanced Electronic Materials, EarlyView.
Reconfigurable intelligent surfaces have become a recent intensive research focus. Based on practical applications, channel strategies for RIS‐assisted terahertz wireless communication systems are categorized into three different types: channel modeling, channel estimation, and channel localization.
Hongjing Wang, Weipeng Wang, Xuan Cong, Shiyu Wang, Gao Li, Sen Gong, Lin Huang, Hongxin Zeng, Yaxin Zhang, Ziqiang Yang   +9 more
wiley   +1 more source

TensorLightning: A Traffic-Efficient Distributed Deep Learning on Commodity Spark Clusters

IEEE Access, 2018
With the recent success of deep learning, the amount of data and computation continues to grow daily. Hence a distributed deep learning system that shares the training workload has been researched extensively. Although a scale-out distributed environment
Seil Lee, Hanjoo Kim, Jaehong Park, Jaehee Jang, Chang-Sung Jeong, Sungroh Yoon   +5 more
doaj   +1 more source

Efficacy of deep learning methods for predicting under-five mortality in 34 low-income and middle-income countries

BMJ Open, 2020
Objectives To explore the efficacy of machine learning (ML) techniques in predicting under-five mortality (U5M) in low-income and middle-income countries (LMICs) and to identify significant predictors of U5M.Design This is a cross-sectional, proof-of ...
Jing Sun, Adeyinka Emmanuel Adegbosin, Bela Stantic   +2 more
doaj   +1 more source

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

Advanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho, Dae‐won Kim, Yujin Kim, Jung‐Heum Na, Yuwon Jeong, Dong‐Yeop Lee, Shinhyun Choi   +6 more
wiley   +1 more source