VR and AR virtual welding for psychomotor skills: a systematic review [0.03%]
基于心理运动技能的虚拟焊接的系统性综述：从VR到AR
Vei Siang Chan,Habibah Norehan Hj Haron,Muhammad Ismail Bin Mat Isham et al.
Vei Siang Chan et al.
Virtual reality (VR) and augmented reality (AR) continue to play an important role in vocational training in the current pandemic and Industrial Revolution 4.0 era. Welding is one of the highly demanded vocational skills for various manufac...
Passenger flow prediction in bus transportation system using deep learning [0.03%]
基于深度学习的公交客流预测方法研究
Nandini Nagaraj,Harinahalli Lokesh Gururaj,Beekanahalli Harish Swathi et al.
Nandini Nagaraj et al.
The forecasting of bus passenger flow is important to the bus transit system's operation. Because of the complicated structure of the bus operation system, it's difficult to explain how passengers travel along different routes. Due to the h...
Exploiting epistemic uncertainty of the deep learning models to generate adversarial samples [0.03%]
利用深度学习模型的认识不确定性生成对抗样本
Omer Faruk Tuna,Ferhat Ozgur Catak,M Taner Eskil
Omer Faruk Tuna
Deep neural network (DNN) architectures are considered to be robust to random perturbations. Nevertheless, it was shown that they could be severely vulnerable to slight but carefully crafted perturbations of the input, termed as adversarial...
Identification of gastric cancer with convolutional neural networks: a systematic review [0.03%]
基于卷积神经网络的胃癌识别：系统性综述研究
Yuxue Zhao,Bo Hu,Ying Wang et al.
Yuxue Zhao et al.
The identification of diseases is inseparable from artificial intelligence. As an important branch of artificial intelligence, convolutional neural networks play an important role in the identification of gastric cancer. We conducted a syst...
Sense understanding of text conversation using temporal convolution neural network [0.03%]
基于时间卷积神经网络的文本对话语义理解
Sandeep Rathor,Sanket Agrawal
Sandeep Rathor
This paper proposes a model which uses Spatio Temporal features for real-time sense understanding of a text conversation. The proposed model uses CNN along with the concept of LSTM to create a new Spatio temporal cell. Furthermore, the prop...
Hei-Chia Wang,Chun-Chieh Chen,Ting-Wei Li
Hei-Chia Wang
With the rapid development of the internet, a large amount of online news has brought readers a variety of information. Some important events last for some time as the event develops or the topic spreads. When readers want to catch up on th...
Deep learning based neural network application for automatic ultrasonic computed tomographic bone image segmentation [0.03%]
基于深度学习的神经网络在自动超声计算机断层骨图像分割中的应用研究
Fradi Marwa,El-Hadi Zahzah,Kais Bouallegue et al.
Fradi Marwa et al.
Deep-learning techniques have led to technological progress in the area of medical imaging segmentation especially in the ultrasound domain. In this paper, the main goal of this study is to optimize a deep-learning-based neural network arch...
A systematic literature review of how and whether social media data can complement traditional survey data to study public opinion [0.03%]
社交媒体数据如何以及在多大程度上能补充传统调查数据来研究公众意见：系统文献综述
Maud Reveilhac,Stephanie Steinmetz,Davide Morselli
Maud Reveilhac
In this article, we review existing research on the complementarity of social media data and survey data for the study of public opinion. We start by situating our review in the extensive literature (N = 187) about the uses, challenges, and...
Medical images lossless recovery based on POB number system and image compression [0.03%]
基于POB数制的医学图像无损恢复及图像压缩编码研究
Qingdan Li,Yao Fu,Zehui Zhang et al.
Qingdan Li et al.
To protect the information integrity of the medical images, this paper proposes a secure lossless recovery scheme for medical images based on image block compression and permutation ordered binary (POB) number system, which includes two par...
Measuring the impact of social drive across social media forums: a case study of COVID-19 [0.03%]
社交媒体论坛上社会驱动影响力的衡量：以COVID-19为例
Mahmoud Oglah Al Hasan Baniata,Sohail Asghar
Mahmoud Oglah Al Hasan Baniata
Users considered Social media forums like Facebook, Twitter and blogs as the most prominent social networks in the present age, where users share their views quickly in words and respond to feedback from other users within no time. This stu...