Results 51 to 60 of about 5,573 (153)

Research on Gene Chip Image Segmentation Algorithm Based on Deep Learning [PDF]

open access: yes, 2017
基因芯片是由数千个基因点组成的一个微阵列,它是一项能够分析基因表达的技术。通过基因表达不仅可以探索人类疾病的潜在遗传原因,还可以应用在环境卫生研究、药物研制与开发、临床诊断和治疗以及癌症检测。基因芯片图像处理在基因表达分析中是一个极其关键的环节,处理的结果直接影响到准确率和精度。基因芯片图像处理主要包括预处理、网格定位、靶点分割和信号提取与分析。本文主要工作围绕以下几点展开: 首先,通过对基因芯片图像预处理分析不同基因点的特征,对其进行灰度转换,对比度增强、滤波去噪等处理进而网格定位 ...
上官亚力
core  

Deep Learning–Driven Surface‐Enhanced Raman Scattering–Lateral Flow Immunoassay With Au Nanostars for High‐Accuracy Respiratory Virus Detection

open access: yesRare Metals, Volume 45, Issue 2, February 2026.
ABSTRACT The high accuracy in surface‐enhanced Raman scattering‐lateral flow immunoassays (SERS–LFIAs) is critical for reliable point‐of‐care testing (POCT) in clinical diagnostics. Conventional approaches are often affected by sampling variability and uneven distribution of immunoprobes, leading to unreliable signal fluctuations.
Shuai Zhao   +9 more
wiley   +1 more source

Research on multi-modal sentiment feature learning of social media content [PDF]

open access: yes, 2016
社交媒体已成为现代社会舆论交流和信息传递的主要平台。针对社交媒体的情感分析对于舆论监控、商业产品导向和股市预测等都具有重大应用价值。但社交媒体内容的多模态性(文本、图片等)让传统的单模态情感分析方法面临许多局限,多模态情感分析技术对跨媒体内容的理解与分析具有重大的理论价值。 多模态情感分析区别于单模态方法的关键问题在于,如何综合利用形态各异的多模态情感信息,来获取整体的情感倾向性,同时考虑单个模态本身在情感表达上的性质。针对该问题,利用社交媒体上的多模态内容在情感表达上所具有的关联性、抽象层级性的特点 ...
李凌霄
core  

A Mini Review on Evolution of High‐Entropy Alloy Design: From Experimental Approaches to Machine Learning Integration

open access: yesRare Metals, Volume 45, Issue 1, January 2026.
ABSTRACT High‐entropy alloys (HEAs) have emerged as a transformative class of materials distinguished by their complex chemical compositions, unique microstructures, and remarkable mechanical and functional properties. Traditionally, the discovery and optimization of HEAs have relied on conventional methods, including trial‐and‐error experimentation ...
Chrispin Ouko Zamzu   +2 more
wiley   +1 more source

基于四川地震预警站网数据的震相检测模型迁移学习研究

open access: yesDizhen xuebao
2023年中国建成了全球规模最大的地震预警网,预警网中的台站配置了速度计、加速度计、简易烈度计(MEMS)等多种地震仪器。目前用于深度学习模型训练的数据集主要由速度计数据组成,不同类型仪器记录的数据在处理时精度会下降。为了解决这一问题,本文使用Yu等(2023)发布的BRNN模型作为预训练模型;然后使用2万6 739条人工标注的四川地区的速度计、加速度计和MEMS数据进行迁移学习。实验结果表明:迁移学习显著提升了模型对加速度计和MEMS预警仪器数据记录到的Pg,Sg震相的检测精度 ...
Yuqi Cai   +6 more
doaj   +1 more source

A Review On Table Recognition Based On Deep Learning

open access: yes, 2023
Table recognition is using the computer to automatically understand the table, to detect the position of the table from the document or picture, and to correctly extract and identify the internal structure and content of the table.
chunqi, Shi, Jiyuan, Shi
core  

CHINA’S LAND FINANCE AS ACTIVE MODE OF LAND DEVELOPMENT AND INFRASTRUCTURE DELIVERY: Reality, History and Prospects

open access: yesInternational Journal of Urban and Regional Research, Volume 50, Issue 1, Page 191-220, January 2026.
Abstract Henry George advocated for capturing land value increases for public ends. The active approach of public authorities organizing and financing land development can help capture higher land value increases, as Hartman and Spit indicate. However, this approach hardly happens in developing countries, where the coalition of private developers and ...
Nannan Xu
wiley   +1 more source

Understanding Student Preparedness to Handle L2 Writing Curriculum Transitions: A Hidden Curriculum Perspective

open access: yesInternational Journal of Applied Linguistics, Volume 35, Issue 4, Page 2063-2077, November 2025.
ABSTRACT Despite the efforts devoted to improving L2 writing pedagogy to promote student writing development, students’ dissatisfactory writing development and outcomes are still reported. Investigating student learning preparedness to navigate L2 writing curriculum transitions may generate new understandings and provide an alternative explanation for ...
Yu Zhou, Shulin Yu
wiley   +1 more source

Study on Parallel Learning Algorithm of Gradient Boosting Decision Tree [PDF]

open access: yes, 2016
GBDT(GradientBoostingDecisionTree)是一个应用广泛、效果好的监督式机器学习模型。它于2001年由Friedman提出,由决策树(DecisionTree)和梯度提升(GradientBoosting)组合而成。它在实践中被证明是一个很高效的模型,被广泛应用于搜索排序,广告点击率预测等,给工业界带来了巨大的效果提升和收益。随着互联网时代的到来,更多的数据可以被获取到。在机器学习中,更多的数据也意味着更好的效果,所以,用大数据来训练机器学习模型是很有必要的 ...
柯国霖
core  

Content Moderation and Community Standards: The Disconnect Between Policy and User Experiences Reporting Harmful and Offensive Content on Social Media

open access: yesPolicy &Internet, Volume 17, Issue 3, September 2025.
ABSTRACT Moderating harmful and offensive content on social media is challenging for digital platforms that seek to balance regulation and censorship across a diverse user group. It is further complicated by discrepancies between platform policies, user expectations and user experiences.
Asher Flynn   +4 more
wiley   +1 more source

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