activity
20182020
most citedChallenges in Vessel Behavior and Anomaly Detection: From Classical Machine Learning to Deep Learning

1 citations · 1 across the 2 of their papers we have counts for

collaborators

7 papers

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.LG2020

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…

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.AI2018

On feature selection and evaluation of transportation mode prediction strategies

Mohammad Etemad, Amilcar Soares Junior, Stan Matwin

Transportation modes prediction is a fundamental task for decision making in smart cities and traffic management systems. Traffic policies designed based on trajectory mining can s…

cs.AI2018

Predicting Crime Using Spatial Features

Fateha Khanam Bappee, Amilcar Soares Junior, Stan Matwin

Our study aims to build a machine learning model for crime prediction using geospatial features for different categories of crime. The reverse geocoding technique is applied to ret…