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Titlebook: Virtual and Augmented Reality for Automobile Industry: Innovation Vision and Applications; Aboul Ella Hassanien,Deepak Gupta,Adam Slowik B

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11#
發(fā)表于 2025-3-23 10:27:40 | 只看該作者
Kirti Aggarwal,Anuja Arora — fertigungsteehnisch betrachtet — die sehr unsauberen Trennfl?chen unbrauehbar sind. Einen grundlegenden Wandel brachten die nunmehr l?ngst abgelaufenen DRP 137588 und insbesondere das Zusatzpatent 143640, die erstmalig den Weg wiesen, wie durch Erhitzen eines Stahlstückes auf seine Entzündungstem
12#
發(fā)表于 2025-3-23 15:42:38 | 只看該作者
13#
發(fā)表于 2025-3-23 19:25:53 | 只看該作者
Autonomous Vehicle Assisted by Heads up Display (HUD) with Augmented Reality Based on Machine Learnify the objects in motion. Accuracy, precision, recall and F-1 score are the analyzed parameters for machine learning-based ARHUD. The simulation results obtained are accuracy of 98%, precision 94%, recall 92.3% and F-1 score 86% in comparison with CNN, ANN and SVM.
14#
發(fā)表于 2025-3-23 23:14:31 | 只看該作者
15#
發(fā)表于 2025-3-24 05:09:30 | 只看該作者
16#
發(fā)表于 2025-3-24 07:49:53 | 只看該作者
Optimal Stacked Sparse Autoencoder Based Traffic Flow Prediction in Intelligent Transportation Systn be adjusted by the use of water wave optimization (WWO) technique. To showcase the enhanced predictive outcome of the OSSAE-TFP technique, a wide range of simulations was carried out on benchmark datasets and the results portrayed the supremacy of the OSSAE-TFP technique over the recent state of a
17#
發(fā)表于 2025-3-24 14:13:25 | 只看該作者
Leverage Computer Vision for Cost-Effective Learning Paradigm,developed ARCore, an SDK that allows the development of augmented reality-based applications. In this virtualized environment, the user can immerse themselves even when they are not physically present. In our model, we have facilitated the user to explore different dimensions of the computer vision
18#
發(fā)表于 2025-3-24 15:38:16 | 只看該作者
Hand Gesture Recognition for Real-Time Game Play Using Background Elimination and Deep Convolution xtract the hand gesture image captured through a mobile/web camera. These hand images have been used to train as well as predict the type of gesture. CNN is used to detect gestures and to render the appropriate motion in the game. The designed human–computer interaction system concludes 98.2% accura
19#
發(fā)表于 2025-3-24 19:57:12 | 只看該作者
20#
發(fā)表于 2025-3-24 23:40:48 | 只看該作者
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