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Jose Luis Vieira Sobrinho, Flavio Henrique Teles Vieira and Alisson Assis Cardoso
The high dimensionality of real-life datasets is one of the biggest challenges in the machine learning field. Due to the increased need for computational resources, the higher the dimension of the input data is, the more difficult the learning task will ...
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Chuanyun Xu, Hang Wang, Yang Zhang, Zheng Zhou and Gang Li
Few-shot learning refers to training a model with a few labeled data to effectively recognize unseen categories. Recently, numerous approaches have been suggested to improve the extraction of abundant feature information at hierarchical layers or multipl...
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Zelang Miao, Renfeng Peng, Wei Wang, Qirong Li, Shuai Chen, Anshu Zhang, Minghui Pu, Ke Li, Qinqin Liu and Changhao Hu
Earthquakes induce landslides worldwide every year that may cause massive fatalities and financial losses. Precise and timely landslide susceptibility mapping (LSM) is significant for landslide hazard assessment and mitigation in earthquake-affected area...
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Emad Arasteh, Ailar Mahdizadeh, Maryam S. Mirian, Soojin Lee and Martin J. McKeown
Parkinson?s disease (PD) is characterized by abnormal brain oscillations that can change rapidly. Tracking neural alternations with high temporal resolution electrophysiological monitoring methods such as EEG can lead to valuable information about altera...
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Jixiang Zhu, Miao Gao, Anmin Zhang, Yingjun Hu and Xi Zeng
In order to detect multi-ship encounter situations and improve the safety of navigation, this paper proposed a model which was able to mine multi-ship encounter situations from Automatic identification system (AIS) data and analyze the encounter spatial-...
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Despoina Mouratidis, Maria Nefeli Nikiforos and Katia Lida Kermanidis
In the past decade, the rapid spread of large volumes of online information among an increasing number of social network users is observed. It is a phenomenon that has often been exploited by malicious users and entities, which forge, distribute, and rep...
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Shuli Wang, Xuewen Li, Xiaomeng Kou, Jin Zhang, Shaojie Zheng, Jinlong Wang and Jibing Gong
Predicting users? next behavior through learning users? preferences according to the users? historical behaviors is known as sequential recommendation. In this task, learning sequence representation by modeling the pairwise relationship between items in ...
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Alessandro Mazzei, Mattia Cerrato, Roberto Esposito and Valerio Basile
In natural language generation, word ordering is the task of putting the words composing the output surface form in the correct grammatical order. In this paper, we propose to apply general learning-to-rank algorithms to the task of word ordering in the ...
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Chih-Chung Hsu, Yi-Xiu Zhuang and Chia-Yen Lee
Generative adversarial networks (GANs) can be used to generate a photo-realistic image from a low-dimension random noise. Such a synthesized (fake) image with inappropriate content can be used on social media networks, which can cause severe problems. Wi...
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Xin Chen and Ying Li
Conventionally, the similarity between two images is measured by the easy-calculating Euclidean distance between their corresponding image feature representations for image retrieval. However, this kind of direct similarity measurement ignores the local ...
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