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: Data Engineering for Smart Systems; Proceedings of SSIC Priyadarsi Nanda,Vivek Kumar Verma,Arka Prokash Ma Conference proceedings 2022 The

[復(fù)制鏈接]
樓主: 根深蒂固
51#
發(fā)表于 2025-3-30 10:33:22 | 只看該作者
Gordon J. Alderink,Blake M. Ashbyted investigators communities, intended to increase the connectivity of data network, principally in an area where formations of traditional networks are unfeasible. However, this network is capable to constitute and heal itself without having a predetermined infrastructure, but with high mobility a
52#
發(fā)表于 2025-3-30 13:24:49 | 只看該作者
53#
發(fā)表于 2025-3-30 18:52:04 | 只看該作者
54#
發(fā)表于 2025-3-30 20:56:05 | 只看該作者
Priyadarsi Nanda,Vivek Kumar Verma,Arka Prokash MaPresents recent research in the field of data engineering.Discusses the outcomes of SSIC 2021, held in Manipal University Jaipur, India.Serves as a reference guide for researchers and practitioners in
55#
發(fā)表于 2025-3-31 03:34:07 | 只看該作者
Lecture Notes in Networks and Systemshttp://image.papertrans.cn/d/image/262793.jpg
56#
發(fā)表于 2025-3-31 08:32:02 | 只看該作者
2367-3370 es as a reference guide for researchers and practitioners inThis book features original papers from the 3rd International Conference on Smart IoT Systems: Innovations and Computing (SSIC 2021), organized by Manipal University, Jaipur, India, during January 22–23, 2021. It discusses scientific works
57#
發(fā)表于 2025-3-31 12:11:59 | 只看該作者
58#
發(fā)表于 2025-3-31 14:34:15 | 只看該作者
Classification and Its Alternatives demand of business nowadays and is a stimulating task. Machine learning and deep learning are spreading its wings in this field for automatic classification of such data and documents. This paper delves into contribution of the researchers in Indian Languages for information retrieval and classification with machine learning.
59#
發(fā)表于 2025-3-31 21:33:03 | 只看該作者
Object Recognition in a Cluttered Scene,lly or partially occluded. In this paper, an object recognition system based on deep learning techniques is proposed. RetinaNet Model has been used for object detection and identification. RetinaNet model has demonstrated to work well with both small scale as well as dense objects.
60#
發(fā)表于 2025-3-31 22:48:12 | 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(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(píng) 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(guó)際 ( 京公網(wǎng)安備110108008328) GMT+8, 2026-1-25 12:42
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
当涂县| 安龙县| 德昌县| 濉溪县| 昌黎县| 光山县| 峨眉山市| 阜新| 吉林省| 康保县| 玛纳斯县| 慈利县| 信丰县| 高雄县| 阿坝县| 黄浦区| 皮山县| 韶关市| 乌拉特中旗| 辽中县| 安岳县| 正定县| 开阳县| 呼和浩特市| 来凤县| 星座| 通城县| 鹿泉市| 清徐县| 浦东新区| 梁平县| 长海县| 通州市| 安化县| 团风县| 巧家县| 黄骅市| 梅河口市| 许昌县| 武山县| 襄城县|