找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問(wèn)微社區(qū)

打印 上一主題 下一主題

Titlebook: Artificial Intelligence and Robotics; 8th International Sy Huimin Lu,Jintong Cai Conference proceedings 2024 The Editor(s) (if applicable)

[復(fù)制鏈接]
樓主: GALL
21#
發(fā)表于 2025-3-25 06:49:05 | 只看該作者
22#
發(fā)表于 2025-3-25 10:58:54 | 只看該作者
Weitere M?glichkeiten — Ausblickd Network (OSAPN). The experimental results show that our method can predict the comments, which are more closely aligned to aesthetic topics than those produced by the previous models. Through the evaluation criteria of image captioning, the specially designed model outperforms other methods.
23#
發(fā)表于 2025-3-25 12:18:26 | 只看該作者
24#
發(fā)表于 2025-3-25 17:39:31 | 只看該作者
25#
發(fā)表于 2025-3-25 22:46:57 | 只看該作者
26#
發(fā)表于 2025-3-26 02:52:33 | 只看該作者
,Two Stream Multi-Attention Graph Convolutional Network for?Skeleton-Based Action Recognition,ich are proposed to enhance the spatio-temporal expression ability of the model. On cross-subject benchmark and cross-view benchmark of NTU-RGB+D datasets, the proposed model achieves 88.60% and 97.16% accuracy respectively, and 35.62% accuracy on the Kinetics dataset. On both datasets, our method outperforms state-of-the-art methods.
27#
發(fā)表于 2025-3-26 08:16:43 | 只看該作者
,Aesthetic Multi-attributes Captioning Network for?Photos,d Network (OSAPN). The experimental results show that our method can predict the comments, which are more closely aligned to aesthetic topics than those produced by the previous models. Through the evaluation criteria of image captioning, the specially designed model outperforms other methods.
28#
發(fā)表于 2025-3-26 11:08:44 | 只看該作者
Improving Road Extraction in Hyperspectral Data with Deep Learning Models,osed method improves the average per-class accuracy by more than 18% over the traditional methods, demonstrating its potential to optimize road extraction from hyperspectral data. Further research can focus on improving the accuracy and efficiency of road network extraction from hyperspectral data.
29#
發(fā)表于 2025-3-26 15:18:35 | 只看該作者
30#
發(fā)表于 2025-3-26 16:53:30 | 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(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 05:40
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
郯城县| 永靖县| 乌鲁木齐市| 洛宁县| 百色市| 洪洞县| 沾化县| 元谋县| 同德县| 江永县| 甘谷县| 阿鲁科尔沁旗| 邵东县| 巩留县| 金沙县| 六枝特区| 柞水县| 兴义市| 老河口市| 大港区| 德格县| 河南省| 杂多县| 安福县| 孟州市| 岑巩县| 利辛县| 金平| 大名县| 米林县| 新沂市| 古蔺县| 宁德市| 姚安县| 汉阴县| 宣化县| 郴州市| 赫章县| 巴东县| 谢通门县| 咸阳市|