找回密碼
 To register

QQ登錄

只需一步，快速開(kāi)始

掃一掃，訪問(wèn)微社區(qū)

打印 上一主題 下一主題

Titlebook: Key Digital Trends in Artificial Intelligence and Robotics; Proceedings of 4th I Luigi Troiano,Alfredo Vaccaro,David Pastor-Escured Confere

[復(fù)制鏈接]
查看: 40563|回復(fù): 52
樓主
發(fā)表于 2025-3-21 19:17:28 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Key Digital Trends in Artificial Intelligence and Robotics
副標(biāo)題Proceedings of 4th I
編輯Luigi Troiano,Alfredo Vaccaro,David Pastor-Escured
視頻videohttp://file.papertrans.cn/543/542557/542557.mp4
概述Presents new technologies and applications in Deep Learning, Artificial Intelligence and robotics.Includes the results from the 4th International Conference on Deep Learning, Artificial Intelligence a
叢書(shū)名稱(chēng)Lecture Notes in Networks and Systems
圖書(shū)封面Titlebook: Key Digital Trends in Artificial Intelligence and Robotics; Proceedings of 4th I Luigi Troiano,Alfredo Vaccaro,David Pastor-Escured Confere
描述.The book (proceedings of the 4th International Conference on Deep Learning, Artificial Intelligence and Robotics (ICDLAIR) 2022) introduces key topics from artificial intelligence algorithms and programming organisations and explains how they contribute to health care, manufacturing, law, finance, retail, real estate, accountancy, digital marketing, and various other fields. Although artificial intelligence (AI) has generated a lot of hype over the past ten years, these consequences on how we live, work, and play are still in their infancy and will likely have a significant impact in the future. The supremacy of AI in areas like speech and picture recognition, navigational apps, personal assistants for smartphones, ride-sharing apps, and many other areas is already well established. The book is primarily meant for academics, researchers, and engineers who want to employ AI applications to address real-world issues. The authors hope that businesses and technology creators will also find it appealing to utilise in industry...?.
出版日期Conference proceedings 2023
關(guān)鍵詞ICDLAIR2022; Deep Learning; Artificial Intelligence; Robotics; Biometric Recognition Systems; Medical Dia
版次1
doihttps://doi.org/10.1007/978-3-031-30396-8
isbn_softcover978-3-031-30395-1
isbn_ebook978-3-031-30396-8Series ISSN 2367-3370 Series E-ISSN 2367-3389
issn_series 2367-3370
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

書(shū)目名稱(chēng)Key Digital Trends in Artificial Intelligence and Robotics影響因子(影響力)




書(shū)目名稱(chēng)Key Digital Trends in Artificial Intelligence and Robotics影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Key Digital Trends in Artificial Intelligence and Robotics網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Key Digital Trends in Artificial Intelligence and Robotics網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Key Digital Trends in Artificial Intelligence and Robotics被引頻次




書(shū)目名稱(chēng)Key Digital Trends in Artificial Intelligence and Robotics被引頻次學(xué)科排名




書(shū)目名稱(chēng)Key Digital Trends in Artificial Intelligence and Robotics年度引用




書(shū)目名稱(chēng)Key Digital Trends in Artificial Intelligence and Robotics年度引用學(xué)科排名




書(shū)目名稱(chēng)Key Digital Trends in Artificial Intelligence and Robotics讀者反饋




書(shū)目名稱(chēng)Key Digital Trends in Artificial Intelligence and Robotics讀者反饋學(xué)科排名




單選投票, 共有 1 人參與投票
 

1票 100.00%

Perfect with Aesthetics
 

0票 0.00%

Better Implies Difficulty
 

0票 0.00%

Good and Satisfactory
 

0票 0.00%

Adverse Performance
 

0票 0.00%

Disdainful Garbage
您所在的用戶(hù)組沒(méi)有投票權(quán)限
沙發(fā)
發(fā)表于 2025-3-21 20:44:53 | 只看該作者
板凳
發(fā)表于 2025-3-22 03:33:55 | 只看該作者
地板
發(fā)表于 2025-3-22 08:12:02 | 只看該作者
5#
發(fā)表于 2025-3-22 09:54:13 | 只看該作者
6#
發(fā)表于 2025-3-22 14:30:46 | 只看該作者
,Bi-RNN and?Bi-LSTM Based Text Classification for?Amazon Reviews,dataset consisting of Amazon reviews into positive and negative. Consumers are able to choose a product solely on these binary text categorizations, neglecting the manual rating provided in the reviews. Recently, Deep Learning (DL) approaches started gaining popularity in E-Commerce applications. DL
7#
發(fā)表于 2025-3-22 18:03:35 | 只看該作者
Resource Utilization Tracking for Fine-Tuning Based Event Detection and Summarization Over Cloud,etrieval, analysis and summarization. The exponential growth of video content needs an effective video summarization which can help in efficient indexing and retrieval of data. The video summariza-tion is a challenging task due to huge amounts of data, redundancy, interview correlation and lighting
8#
發(fā)表于 2025-3-23 00:57:43 | 只看該作者
,Automatic Fake News Detection: A Review Article on?State of?the?Art,tribute fake news and generate propaganda to sway public opinion since the dawn. However, new obstacles in detecting fake news have evolved with modern social media. Moreover, false news dissemination is becoming more like a business, with individuals being paid to generate bogus information, making
9#
發(fā)表于 2025-3-23 05:25:27 | 只看該作者
Cascaded 3D V-Net for Fully Automatic Segmentation and Classification of Brain Tumor Using Multi-chative for saving human life. BT segmentation and categorization are crucial tasks involved in BT recognition. Many existing approaches have been developed for detecting BTs. But, the existing models do not focus on segmenting and categorizing diverse categories of BTs. Further, these existing models
10#
發(fā)表于 2025-3-23 06:26:21 | 只看該作者
,Computing Physical Stress During Working Shift with?Deep Neural Networks,r vision, techniques and pose estimation algorithms in industrial context to optimise production task and to build more ergonomic workstations. The approach is based on a state of the art model for pose estimation; the output of the model is then used as abstraction of people activities during work
 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(ài)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, 2025-10-10 10:31
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
崇明县| 天全县| 济阳县| 太和县| 遂川县| 海门市| 区。| 开阳县| 成安县| 八宿县| 营山县| 桐柏县| 中山市| 通州市| 县级市| 湘潭县| 滦南县| 始兴县| 新巴尔虎右旗| 阿坝县| 宁化县| 白朗县| 巩义市| 抚顺市| 泾阳县| 静安区| 奉化市| 江达县| 胶南市| 宜章县| 游戏| 台安县| 沧州市| 乐安县| 枣阳市| 甘孜县| 岚皋县| 朔州市| 陇川县| 甘孜| 山阳县|