79 citations · 603 across the 47 of their papers we have counts for
12 papers · 1 filter
COVID-19 Pandemic: Identifying Key Issues using Social Media and Natural Language Processing
Oladapo Oyebode, Chinenye Ndulue, Dinesh Mulchandani +6
The COVID-19 pandemic has affected people's lives in many ways. Social media data can reveal public perceptions and experience with respect to the pandemic, and also reveal factors…
SemEval-2020 Task 5: Counterfactual Recognition
Xiaoyu Yang, Stephen Obadinma, Huasha Zhao +3
We present a counterfactual recognition (CR) task, the shared Task 5 of SemEval-2020. Counterfactuals describe potential outcomes (consequents) produced by actions or circumstances…
Pay Attention to Evolution: Time Series Forecasting with Deep Graph-Evolution Learning
Gabriel Spadon, Shenda Hong, Bruno Brandoli +3
Time-series forecasting is one of the most active research topics in artificial intelligence. Applications in real-world time series should consider two factors for achieving relia…
Learn Faster and Forget Slower via Fast and Stable Task Adaptation
Farshid Varno, Lucas May Petry, Lisa Di Jorio +1
Training Deep Neural Networks (DNNs) is still highly time-consuming and compute-intensive. It has been shown that adapting a pretrained model may significantly accelerate this proc…
Analyzing the Impact of Foursquare and Streetlight Data with Human Demographics on Future Crime Prediction
Fateha Khanam Bappee, Lucas May Petry, Amilcar Soares +1
Finding the factors contributing to criminal activities and their consequences is essential to improve quantitative crime research. To respond to this concern, we examine an extens…
Implicit Class-Conditioned Domain Alignment for Unsupervised Domain Adaptation
Xiang Jiang, Qicheng Lao, Stan Matwin +1
We present an approach for unsupervised domain adaptation---with a strong focus on practical considerations of within-domain class imbalance and between-domain class distribution s…
Give more data, awareness and control to individual citizens, and they will help COVID-19 containment
Mirco Nanni, Gennady Andrienko, Albert-László Barabási +36
The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the phase 2 of the pandemic, when…
Challenges in Vessel Behavior and Anomaly Detection: From Classical Machine Learning to Deep Learning
Lucas May Petry, Amilcar Soares, Vania Bogorny +2
The global expansion of maritime activities and the development of the Automatic Identification System (AIS) have driven the advances in maritime monitoring systems in the last dec…
Using Deep Reinforcement Learning Methods for Autonomous Vessels in 2D Environments
Mohammad Etemad, Nader Zare, Mahtab Sarvmaili +3
Unmanned Surface Vehicles technology (USVs) is an exciting topic that essentially deploys an algorithm to safely and efficiently performs a mission. Although reinforcement learning…
Wise Sliding Window Segmentation: A classification-aided approach for trajectory segmentation
Mohammad Etemad, Zahra Etemad, Amilcar Soares +3
Large amounts of mobility data are being generated from many different sources, and several data mining methods have been proposed for this data. One of the most critical steps for…
Performance of a Deep Neural Network at Detecting North Atlantic Right Whale Upcalls
Oliver S. Kirsebom, Fabio Frazao, Yvan Simard +3
Passive acoustics provides a powerful tool for monitoring the endangered North Atlantic right whale ( ), but robust detection algorithms are needed to handle…
Black Box Explanation by Learning Image Exemplars in the Latent Feature Space
Riccardo Guidotti, Anna Monreale, Stan Matwin +1
We present an approach to explain the decisions of black box models for image classification. While using the black box to label images, our explanation method exploits the latent…