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: Smart Trends in Computing and Communications; Proceedings of Smart Tomonobu Senjyu,Chakchai So-In,Amit Joshi Conference proceedings 2023 Th

[復制鏈接]
樓主: 啞劇表演
21#
發(fā)表于 2025-3-25 03:36:50 | 只看該作者
Wireless SDN: A Perspective for Handover Management, the three categories of networks: Wireless LAN, Wireless sensor, and cellular are considered in this article. After delving into the present SDN-based handover management efforts, the opportunities to further improve the operation and performance of handover management with the help of SDN are also
22#
發(fā)表于 2025-3-25 08:49:00 | 只看該作者
23#
發(fā)表于 2025-3-25 13:23:38 | 只看該作者
Secure QR Code Transactions Using Mobile Banking App,niques such as hashing, role-based authentication mechanism, prevention of SQL injection attacks, and tracking MAC address of a user. The possibilities of QR code hacks are presented and the solutions are proposed. The double spending problem is tracked.
24#
發(fā)表于 2025-3-25 16:24:45 | 只看該作者
A Clustering-Based Approach to Feature Selection for Breast-Cancer Classification,ramework to perform feature selection for classification purpose by using data clustering and optimization methods. At the first stage, the proposed approach employs a genetic algorithm to select the best subset of characteristics using clustering validation as an objective function instead of class
25#
發(fā)表于 2025-3-25 21:29:00 | 只看該作者
26#
發(fā)表于 2025-3-26 02:53:57 | 只看該作者
27#
發(fā)表于 2025-3-26 07:31:04 | 只看該作者
Integrating Hybrid Feature Extraction Techniques with Support Vector Machine for Efficient Facial Ef our paper. In this paper, we used technologies like LBP, GLCM, and Gabor filter to extract aspects of images. For training the model, we used the CK?+?dataset that contains 24,282 images in the training set. In this, Support Vector Machine (SVM) is applied for the classification of emotions using
28#
發(fā)表于 2025-3-26 08:59:52 | 只看該作者
,Classification of?ISL Using Pose and?Object Detection-Based Techniques,pproaches for the classification of Indian Sign Language: (a) the object detection-based approach utilizes a model built on Scaled-YOLOv4 architecture which performs a frame-by-frame inference and (b) the Pose-based approach utilizes an LSTM model which takes the skeletal pose landmarks from Mediapi
29#
發(fā)表于 2025-3-26 14:43:52 | 只看該作者
30#
發(fā)表于 2025-3-26 20:05:44 | 只看該作者
 關于派博傳思  派博傳思旗下網站  友情鏈接
派博傳思介紹 公司地理位置 論文服務流程 影響因子官網 吾愛論文網 大講堂 北京大學 Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經驗總結 SCIENCEGARD IMPACTFACTOR 派博系數 清華大學 Yale Uni. Stanford Uni.
QQ|Archiver|手機版|小黑屋| 派博傳思國際 ( 京公網安備110108008328) GMT+8, 2026-1-29 07:41
Copyright © 2001-2015 派博傳思   京公網安備110108008328 版權所有 All rights reserved
快速回復 返回頂部 返回列表
竹山县| 曲松县| 十堰市| 益阳市| 修文县| 丰原市| 额敏县| 北海市| 米林县| 文昌市| 郧西县| 天长市| 华坪县| 湖北省| 钦州市| 安福县| 平江县| 马公市| 滁州市| 上栗县| 城口县| 焦作市| 邹城市| 土默特右旗| 宜兰县| 云林县| 寿光市| 塔河县| 交城县| 上饶市| 石屏县| 乡城县| 樟树市| 伽师县| 高邑县| 阳高县| 德昌县| 上饶县| 台安县| 宣化县| 金昌市|