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: Computer Vision Systems; 14th International C Henrik I. Christensen,Peter Corke,Markus Vincze Conference proceedings 2023 The Editor(s) (if

[復(fù)制鏈接]
樓主: tornado
41#
發(fā)表于 2025-3-28 14:53:15 | 只看該作者
WiFi CSI-Based Long-Range Through-Wall Human Activity Recognition with?the?ESP32constrained environments while preserving visual privacy. Despite the presence of numerous WiFi-enabled devices around us, few expose CSI to users, resulting in a lack of sensing hardware options. Recently, variants of the Espressif ESP32 have emerged as potential low-cost, easy-to-deploy solutions
42#
發(fā)表于 2025-3-28 20:39:29 | 只看該作者
PseudoDepth-SLR: Generating Depth Data for?Sign Language Recognitionth information from RGB data to boost performance and enable generalizability in scenarios where depth data is not available. For the depth generation, we rely on an approach that utilizes vision transformers as a backbone for depth prediction. We examine the effect of pseudo depth data on the perfo
43#
發(fā)表于 2025-3-29 00:04:26 | 只看該作者
Slovo: Russian Sign Language Datasetring and hearing societies. In addition, the sign language in each country differs significantly, which obliges the creation of new data for each of them. This paper presents the Russian Sign Language (RSL) video dataset Slovo, produced using crowdsourcing platforms. The dataset contains 20,000 Full
44#
發(fā)表于 2025-3-29 05:49:48 | 只看該作者
Non-contact Heart Rate Monitoring: A Comparative Study of Computer Vision and Radar Approachesg HR measurement into Driver Monitoring Systems (DMS), providing physiological measurements to help address long-existing road safety issues by minimising human error. In real-world driving scenarios, the HR must be measured using non-contact approaches that avoid distracting or restricting the driv
45#
發(fā)表于 2025-3-29 10:15:26 | 只看該作者
CFAB: An Online Data Augmentation to?Alleviate the?Spuriousness of?Classification on?Medical Ultrasoriousness in CNNs usually occurs in building connections between the background of images and labels. Such spurious correlation limits the generalizability of CNNs in classification tasks. Changing backgrounds and foregrounds of original samples can reduce the spuriousness in natural image classific
46#
發(fā)表于 2025-3-29 12:56:01 | 只看該作者
47#
發(fā)表于 2025-3-29 18:02:10 | 只看該作者
DeepLabV3+ Ensemble for?Diagnosis of?Cardiac Transplant Rejection regular invasive and time-consuming biopsies followed by histopathological analysis. Deep learning has the potential to significantly enhance speed and objectivity and introduce new information from the obtained sample to increase the chances of predicting rejection. Our study presents several deep
48#
發(fā)表于 2025-3-29 23:00:43 | 只看該作者
49#
發(fā)表于 2025-3-30 00:40:30 | 只看該作者
SIFT-Guided Saliency-Based Augmentation for?Weed Detection in?Grassland Images: Fusing Classic Compuis paper investigates how the density of structural features can be used to assist the training process of a Deep-Learning-based object detector. SIFT keypoint density is used to create overlay masks to augment images, emphasizing low-density areas—typically corresponding to weed plants. Our method
50#
發(fā)表于 2025-3-30 06:34:52 | 只看該作者
Key Point-Based Orientation Estimation of?Strawberries for?Robotic Fruit Pickingobotic harvester requires the precise location and orientation of the fruit to effectively plan the trajectory of the end effector. The current methods for estimating fruit orientation employ either complete 3D information registered from multiple views or rely on fully-supervised learning technique
 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, 2025-10-20 14:27
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
宁远县| 石阡县| 休宁县| 铁岭县| 荔浦县| 通城县| 安溪县| 沿河| 滁州市| 涞水县| 杨浦区| 遂川县| 会东县| 瑞安市| 崇州市| 将乐县| 青神县| 西乌| 阜康市| 深州市| 西城区| 昌江| 托克逊县| 肃北| 许昌市| 凤冈县| 竹山县| 庆元县| 深水埗区| 平江县| 阜新市| 定结县| 长垣县| 安新县| 楚雄市| 吕梁市| 邹城市| 望奎县| 淅川县| 上饶县| 屏边|