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: Advances in System-Integrated Intelligence; Proceedings of the 6 Maurizio Valle,Dirk Lehmhus,Klaus-Dieter Thoben Conference proceedings 202

[復制鏈接]
樓主: Nixon
11#
發(fā)表于 2025-3-23 11:57:04 | 只看該作者
Towards a?Trade-off Between Accuracy and?Computational Cost for?Embedded Systems: A Tactile Sensing nt algorithms. Results show that the best performance, when the computational cost is not relevant, is achieved by the fully–connected neural network using 16 features, while, when the computational cost matters, the loss function showed that the kernel SVM with 4 features has the best performance.
12#
發(fā)表于 2025-3-23 16:34:09 | 只看該作者
13#
發(fā)表于 2025-3-23 21:27:17 | 只看該作者
David B. Mertz,David E. McCauleyystem is not available or too complex. The proposed approach is currently under evaluation in the water distribution system of the Milan (Italy) water main. The application of the approach to synthetic data shows its ability of reducing the energy consumption, while ensuring a good quality of service.
14#
發(fā)表于 2025-3-24 01:12:08 | 只看該作者
15#
發(fā)表于 2025-3-24 02:43:26 | 只看該作者
16#
發(fā)表于 2025-3-24 07:08:20 | 只看該作者
Machine Learning Based Reconstruction of Process Forcesches show different results depending on the milling center. Only for the LSTM an error lower than 30?N is achieved for both machine tools. Independent of the ML approach, the results strongly depend on the selection of milling processes used for training.
17#
發(fā)表于 2025-3-24 12:48:20 | 只看該作者
18#
發(fā)表于 2025-3-24 15:56:13 | 只看該作者
An Optimized Heart Rate Detection System Based on?Low-Power Microcontroller Platforms for?Biosignal ed on the RISC-V PULP platform. Experimental results show that our approach achieves an accuracy above 99.5%, comparable to the state-of-the-art solutions, and an energy efficiency that is one order of magnitude better than other software solutions.
19#
發(fā)表于 2025-3-24 19:04:48 | 只看該作者
https://doi.org/10.1007/978-3-030-78803-2actors, as well as the implementation of an object recognition, are investigated. The following paper addresses the question of the extent to which manual assembly processes can be reliably derived from visual sensor data and classified by machine learning algorithms.
20#
發(fā)表于 2025-3-24 23:19:45 | 只看該作者
 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, 2025-10-24 04:27
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
慈利县| 平邑县| 榆中县| 南岸区| 罗源县| 嘉禾县| 长垣县| 通辽市| 鲁甸县| 建德市| 姚安县| 额尔古纳市| 三河市| 郁南县| 洛浦县| 平邑县| 如东县| 涟源市| 银川市| 连云港市| 沙坪坝区| 梅州市| 合阳县| 四子王旗| 栾川县| 米易县| 普兰县| 康平县| 郯城县| 桦甸市| 壶关县| 昌邑市| 崇义县| 江都市| 文成县| 宁城县| 耿马| 萨嘎县| 建宁县| 东港市| 宣汉县|