activity
20182020
most citedDiscovering Heterogeneous Subsequences for Trajectory Classification

2 citations · 3 across the 3 of their papers we have counts for

collaborators

6 papers

cs.NE2020

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…

cs.CY2020

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…

cs.LG20201 cited

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…

cs.LG2019

Unsupervised Behavior Change Detection in Multidimensional Data Streams for Maritime Traffic Monitoring

Lucas May Petry, Amilcar Soares, Vania Bogorny +1

The worldwide growth of maritime traffic and the development of the Automatic Identification System (AIS) has led to advances in monitoring systems for preventing vessel accidents…

cs.LG20192 cited

Discovering Heterogeneous Subsequences for Trajectory Classification

Carlos Andres Ferrero, Lucas May Petry, Luis Otavio Alvares +2

In this paper we propose a new parameter-free method for trajectory classification which finds the best trajectory partition and dimension combination for robust trajectory classif…

cs.SI2018

Traj2User: exploiting embeddings for computing similarity of users mobile behavior

Andrea Esuli, Lucas May Petry, Chiara Renso +1

Semantic trajectories are high level representations of user movements where several aspects related to the movement context are represented as heterogeneous textual labels. With t…