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: Electrical and Computer Engineering; First International Muhammet Nuri Seyman Conference proceedings 2022 ICST Institute for Computer Scie

[復(fù)制鏈接]
樓主: 閘門
41#
發(fā)表于 2025-3-28 16:57:00 | 只看該作者
42#
發(fā)表于 2025-3-28 22:04:24 | 只看該作者
43#
發(fā)表于 2025-3-29 02:09:52 | 只看該作者
44#
發(fā)表于 2025-3-29 05:33:31 | 只看該作者
https://doi.org/10.1007/978-3-476-03713-8 technique has been implemented on the Android operating system. The proposed method delivers about 3 frames per second for 360p video on the Android operating system. It is extremely feasible to increase this real-time performance by employing more powerful hardware.
45#
發(fā)表于 2025-3-29 09:36:06 | 只看該作者
https://doi.org/10.1007/978-3-642-11672-8 proposed CNN is found to give a correct classification rate (CCR) of 72.71%, the CCR reached the level of average 83.51% by using 4 channels. Also, this reduced the training time from 626 to 306?s. Therefore, the results show that usage of specific channels increases the classification accuracy and reduces the time required for training.
46#
發(fā)表于 2025-3-29 14:19:18 | 只看該作者
https://doi.org/10.1007/3-7643-7814-X a data model was created by first deriving the characteristics and values of certain types of sensors, and then a sensor application ontology was created using the OWL language. An application program was then developed using the Java programming language and the sensor application ontology developed was queried through the SPARQL query language.
47#
發(fā)表于 2025-3-29 19:29:06 | 只看該作者
48#
發(fā)表于 2025-3-29 22:41:39 | 只看該作者
49#
發(fā)表于 2025-3-30 03:06:43 | 只看該作者
50#
發(fā)表于 2025-3-30 04:21:01 | 只看該作者
Multi Channel EEG Based Biometric System with a Custom Designed Convolutional Neural Network proposed CNN is found to give a correct classification rate (CCR) of 72.71%, the CCR reached the level of average 83.51% by using 4 channels. Also, this reduced the training time from 626 to 306?s. Therefore, the results show that usage of specific channels increases the classification accuracy and reduces the time required for training.
 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(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-12 06:21
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(fù) 返回頂部 返回列表
原平市| 清河县| 福州市| 阳新县| 鹤壁市| 天峻县| 繁昌县| 崇阳县| 贵定县| 定兴县| 汕尾市| 永嘉县| SHOW| 鄂托克前旗| 调兵山市| 固安县| 哈巴河县| 宁陕县| 烟台市| 建德市| 淳安县| 黑水县| 建始县| 赤水市| 崇义县| 循化| 阳泉市| 永登县| 洪江市| 沛县| 静宁县| 长兴县| 万源市| 崇州市| 巴彦淖尔市| 南丹县| 子长县| 如皋市| 闵行区| 成都市| 上思县|