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A review on artificial intelligence in high-speed rail

Mingjia Yin, Kang Li, Xiaoqing Cheng
2020 Transportation Safety and Environment  
High-speed rail (HSR) has brought a number of social and economic benefits, such as shorter trip times for journeys of between one and five hours; safety, security, comfort and on-time commuting for passengers  ...  Finally, a framework of future HSR systems where AI is expected to play a key role is provided.  ...  Acknowledgements This research work is partially supported by the State Key Laboratory of Rail Traffic Control and Safety (Contract No. RCS2019K005, Beijing Jiaotong University).  ... 
doi:10.1093/tse/tdaa022 fatcat:lwxjywyk5jcb7leh6vesftwgze

Towards Assisting the Visually Impaired: A Review on Techniques for Decoding the Visual Data from Chart Images

K C Shahira, A Lijiya
2021 IEEE Access  
The extracted chart data can be provided as alt-text to the visually impaired people and enable reasoning on these charts. Today, machine learning algorithms generate visualisation of big data.  ...  Generative adversarial networks (GAN) can be used for data augmentation as it can generate new images to enrich the diversity of inputs.  ... 
doi:10.1109/access.2021.3069205 fatcat:xlean3gmpfb6tpvnye7ougmyye

A survey on predicting oil spills by studying its causes using deep learning techniques

Mona Mohamed Nasr, Fahd Kamal Kamel, Yasmen Samhan Abd Elwahab
2021 Indonesian Journal of Electrical Engineering and Computer Science  
an accident but it needs a sufficient data and a powerful technique such as deep learning techniques that give very precise results and by using this tool an Intelligent Model will build to predict oil  ...  <span>It's so easy to know the accidents as it's already happened and solving these accidents is immediately handled, but searching for a solution for these accidents, don't deny the existence of reasons  ...  Data from the Spanish Ministry of Jobs and Social Security was used between 2005 and 2015.  ... 
doi:10.11591/ijeecs.v22.i1.pp580-589 fatcat:sub5427egnfstbctdzck4w7zdi


2021 2021 National Conference on Communications (NCC)  
In this talk, I will present methods for combining DNNs with traditional model-based algorithms.  ...  In addition, even though data sizes are increasing, they also have underlying structure, thus providing algorithm designers with opportunities to exploit this structure for faster computation.  ...  and Big Data.  ... 
doi:10.1109/ncc52529.2021.9530194 fatcat:ahdw5ezvtrh4nb47l2qeos3dwq

Efficient Automated Processing of the Unstructured Documents using Artificial Intelligence: A Systematic Literature Review and Future Directions

Dipali Baviskar, Swati Ahirrao, Vidyasagar Potdar, Ketan Kotecha
2021 IEEE Access  
DL models are generally trained end-to-end, manual feature extraction is not required.  ...  AI-based solutions possess CV and NLP capabilities combined with RPA or OCR workflows, to provide an end-to-end automation solutions.  ... 
doi:10.1109/access.2021.3072900 fatcat:lrbzlmo5gnczhadnrxd2aoqz4u

CHAMELEON: A Deep Learning Meta-Architecture for News Recommender Systems [Phd. Thesis] [article]

Gabriel de Souza Pereira Moreira
2019 arXiv   pre-print
problem, when compared to other traditional and state-of-the-art session-based recommendation algorithms.  ...  All those characteristics are explicitly modeled on this research by a contextual hybrid session-based recommendation approach using Recurrent Neural Networks.  ...  They are specially useful in big data applications, because SGD allows the network to be incrementally trained in steps composed by a single sample or by a mini-batch of samples (Mini-Batch Gradient Descent  ... 
arXiv:2001.04831v1 fatcat:x2k3u26i4jebzjlesswnncfepq