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: Biometric Recognition; 16th Chinese Confere Weihong Deng,Jianjiang Feng,Zhaofeng He Conference proceedings 2022 The Editor(s) (if applicabl

[復(fù)制鏈接]
樓主: 小天使
21#
發(fā)表于 2025-3-25 04:00:45 | 只看該作者
An Overview and Forecast of Biometric Recognition Technology Used in Forensic Sciencependent intellectual property rights. Biometric recognition technologies require increasing investment and targeted niche research if they are to play a more significant role in forensic science in the future.
22#
發(fā)表于 2025-3-25 08:36:24 | 只看該作者
23#
發(fā)表于 2025-3-25 14:26:13 | 只看該作者
Estimation of Gaze-Following Based on Transformer and the Guiding Offsetng offset to facilitate the training of gaze pathway and we add the channel attention module. We use Transformer to capture the relationship between the person and the predicted target in the heatmap pathway. Experimental results have demonstrated the effectiveness of our solution on GazeFollow dataset and DL Gaze dataset.
24#
發(fā)表于 2025-3-25 17:38:18 | 只看該作者
https://doi.org/10.1057/9780230502666 only has global and local correlation to achieve accurate extraction of veins, but also enables the model to maintain its lightweight characteristics. Our approach achieves good results on the public finger vein dataset SDU-FV, MMCBNU_6000.
25#
發(fā)表于 2025-3-25 22:34:34 | 只看該作者
26#
發(fā)表于 2025-3-26 03:28:50 | 只看該作者
A Lightweight Segmentation Network Based on Extraction only has global and local correlation to achieve accurate extraction of veins, but also enables the model to maintain its lightweight characteristics. Our approach achieves good results on the public finger vein dataset SDU-FV, MMCBNU_6000.
27#
發(fā)表于 2025-3-26 04:56:00 | 只看該作者
28#
發(fā)表于 2025-3-26 10:12:32 | 只看該作者
29#
發(fā)表于 2025-3-26 14:46:11 | 只看該作者
Conclusion: Community and Transcendencedifferent types of adversarial faces. Experimental results over adversarial examples and face forgery attacks show that the proposed detection method is effective with better generalizability and more adversarially robust comparing with previous methods.
30#
發(fā)表于 2025-3-26 19:04:01 | 只看該作者
Disentanglement of?Deep Features for?Adversarial Face Detectiondifferent types of adversarial faces. Experimental results over adversarial examples and face forgery attacks show that the proposed detection method is effective with better generalizability and more adversarially robust comparing with previous methods.
 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| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-13 22:12
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
恩施市| 阿克| 宜春市| 密山市| 永州市| 祁门县| 荆门市| 林西县| 大安市| 巩义市| 平原县| 岳西县| 西城区| 小金县| 乐都县| 静安区| 海门市| 晋江市| 仙游县| 宝山区| 息烽县| 德化县| 深水埗区| 中江县| 顺昌县| 怀来县| 石屏县| 南丰县| 任丘市| 东乡族自治县| 徐汇区| 鄂州市| 女性| 广丰县| 蕲春县| 宾川县| 白朗县| 清流县| 青冈县| 汝州市| 汕尾市|