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: Intelligent Sustainable Systems; Proceedings of ICISS Jennifer S. Raj,Ram Palanisamy,Yong Shi Conference proceedings 2022 The Editor(s) (if

[復(fù)制鏈接]
樓主: 可入到
11#
發(fā)表于 2025-3-23 09:48:31 | 只看該作者
,Impact of Segmentation Techniques for Condit?on Monitor?ng of Electrical Equipments from Thermal Imnique is proposed to isolate the Region of Interest. The performance of the proposed technique is compared with that of the conventional segmentation techniques. IACM removes the undesirable regions and is successful in detecting the Region of Interest of any shape and size.
12#
發(fā)表于 2025-3-23 17:13:50 | 只看該作者
2367-3370 rence resource for researchers and practitioners in academia.This book features research papers presented at the 4th?International Conference on Intelligent Sustainable Systems (ICISS 2021), held at SCAD College of Engineering and Technology, Tirunelveli, Tamil Nadu, India, during February 26–27, 20
13#
發(fā)表于 2025-3-23 21:24:54 | 只看該作者
14#
發(fā)表于 2025-3-23 23:26:41 | 只看該作者
Performance Evaluation of Hierarchical Clustering Protocols in WSN Using MATLAB,ralized LEACH, SEP, DEEC, and developed DEEC protocols under different scenarios such as change in the sink position and change in the area. We evaluated and compared them on performance metrics such as network lifetime, throughput, and energy consumption.
15#
發(fā)表于 2025-3-24 05:27:10 | 只看該作者
16#
發(fā)表于 2025-3-24 07:29:01 | 只看該作者
17#
發(fā)表于 2025-3-24 13:05:30 | 只看該作者
18#
發(fā)表于 2025-3-24 18:30:25 | 只看該作者
19#
發(fā)表于 2025-3-24 19:18:11 | 只看該作者
,Deep Learning-Based Approach for Parkinson’s Disease Detection Using Region of Interest,ed an algorithm to identify the most discriminative range of MRI slices at the subject level to differentiate between Normal Cohorts (NC) and Parkinson’s Disease (PD) subjects. We have also focused on handling data leakage and verified the model generalizability using Stratified k-fold cross-validation.
20#
發(fā)表于 2025-3-24 23:11:43 | 只看該作者
Deep Learning in Precision Medicine,terdisciplinary domain, healthcare system is now amalgamated with advance AI domains like Deep Learning, Machine Learning, Big Data, etc. The paper summarizes the applications of Deep Learning in several medical sectors and discusses various algorithms adopted by researchers to include the power of Deep Learning in current medical system.
 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 期刊點評 投稿經(jīng)驗總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) 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, 2026-2-7 20:04
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(fù) 返回頂部 返回列表
盘山县| 沿河| 丘北县| 伊宁县| 达日县| 双牌县| 绥中县| 建湖县| 左贡县| 庐江县| 桃园县| 嘉善县| 清河县| 罗江县| 柳河县| 太仆寺旗| 阜康市| 桂林市| 北海市| 福泉市| 景泰县| 元氏县| 外汇| 甘谷县| 黄浦区| 称多县| 正安县| 阜宁县| 利川市| 伊金霍洛旗| 潼南县| 叶城县| 定南县| 增城市| 荔波县| 琼海市| 哈尔滨市| 炎陵县| 壶关县| 江门市| 建水县|