找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Big Data and Security; 5th International Co Yuan Tian,Tinghuai Ma,Muhammad Khurram Khan Conference proceedings 2024 The Editor(s) (if appli

[復制鏈接]
51#
發(fā)表于 2025-3-30 11:32:59 | 只看該作者
52#
發(fā)表于 2025-3-30 13:28:25 | 只看該作者
53#
發(fā)表于 2025-3-30 20:34:25 | 只看該作者
1865-0929 organized in topical sections as follows:?..Part One:?Big Data & New Method and?Artificial Intelligence & Machine Learning..Part Two:?Data Technology & Network Security and?IoT Security & Privacy Protection..978-981-97-4389-6978-981-97-4390-2Series ISSN 1865-0929 Series E-ISSN 1865-0937
54#
發(fā)表于 2025-3-31 00:01:42 | 只看該作者
The Development of Metalinguistic Abilityhis issue, the method called asymptotic PINNs (A-PINNs) is proposed, which combines the prior knowledge provided by the Shishkin mesh with domain decomposition methods to solve SPDEs effectively. Numerical results indicate that our method shows superiority in handling the singularly perturbed property of SPDEs.
55#
發(fā)表于 2025-3-31 02:00:08 | 只看該作者
56#
發(fā)表于 2025-3-31 08:58:51 | 只看該作者
Big Data and Security978-981-97-4390-2Series ISSN 1865-0929 Series E-ISSN 1865-0937
57#
發(fā)表于 2025-3-31 11:17:49 | 只看該作者
The Development of Metalinguistic Abilityon models have been implemented end-to-end and achieve remarkable performance. To achieve better results on the regions of non-textures, boundaries, and tiny details, it is necessary to effectively combine global context information. However, current models rely on intricate cascade structures or st
58#
發(fā)表于 2025-3-31 16:34:34 | 只看該作者
The Development of Metalinguistic Abilityand phenomena defined by partial differential equations (PDEs). However, PINNs fail to solve PDEs with special properties, such as singularly perturbed differential equations (SPDEs). SPDEs tend to have boundary layers, where the value of the solution increases or decreases drastically. To address t
59#
發(fā)表于 2025-3-31 20:51:11 | 只看該作者
60#
發(fā)表于 2025-4-1 01:00:47 | 只看該作者
https://doi.org/10.1007/978-3-642-74124-1ess to increase productivity. Automating the defect detection process using deep learning such as the YOLO (You Only Look Once) algorithm has shown remarkable performance in object detection tasks. Further integrating the YOLO algorithm with BADGE (Batch Active learning by Diverse Gradient Embedding
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學 Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經(jīng)驗總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學 Yale Uni. Stanford Uni.
QQ|Archiver|手機版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-16 03:04
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復 返回頂部 返回列表
道真| 宁都县| 鱼台县| 霞浦县| 新源县| 瑞安市| 巩留县| 白银市| 乌拉特中旗| 时尚| 澄迈县| 烟台市| 巴彦淖尔市| 法库县| 绥阳县| 台安县| 铜山县| 普格县| 安平县| 武陟县| 开江县| 阿克苏市| 资阳市| 峨山| 静安区| 邵阳县| 三亚市| 浦北县| 保山市| 万荣县| 台中市| 宁武县| 永和县| 和龙市| 永州市| 潜江市| 香河县| 手游| 化德县| 浙江省| 阳高县|