Big trajectory data mining: A survey of methods, applications, and services
The increasingly wide usage of smart infrastructure and location-aware terminals has
helped increase the availability of trajectory data with rich spatiotemporal information. The …
helped increase the availability of trajectory data with rich spatiotemporal information. The …
How to compare movement? A review of physical movement similarity measures in geographic information science and beyond
P Ranacher, K Tzavella - Cartography and geographic information …, 2014 - Taylor & Francis
In geographic information science, a plethora of different approaches and methods is used
to assess the similarity of movement. Some of these approaches term two moving objects …
to assess the similarity of movement. Some of these approaches term two moving objects …
Trajectory clustering: a partition-and-group framework
Existing trajectory clustering algorithms group similar trajectories as a whole, thus
discovering common trajectories. Our key observation is that clustering trajectories as a …
discovering common trajectories. Our key observation is that clustering trajectories as a …
Trajectory outlier detection: A partition-and-detect framework
Outlier detection has been a popular data mining task. However, there is a lack of serious
study on outlier detection for trajectory data. Even worse, an existing trajectory outlier …
study on outlier detection for trajectory data. Even worse, an existing trajectory outlier …
TraClass trajectory classification using hierarchical region-based and trajectory-based clustering
Trajectory classification, ie, model construction for predicting the class labels of moving
objects based on their trajectories and other features, has many important, real-world …
objects based on their trajectories and other features, has many important, real-world …
Incremental clustering for trajectories
Trajectory clustering has played a crucial role in data analysis since it reveals underlying
trends of moving objects. Due to their sequential nature, trajectory data are often received …
trends of moving objects. Due to their sequential nature, trajectory data are often received …
Logo-net: Large-scale deep logo detection and brand recognition with deep region-based convolutional networks
Logo detection from images has many applications, particularly for brand recognition and
intellectual property protection. Most existing studies for logo recognition and detection are …
intellectual property protection. Most existing studies for logo recognition and detection are …
Logo-2k+: A large-scale logo dataset for scalable logo classification
Logo classification has gained increasing attention for its various applications, such as
copyright infringement detection, product recommendation and contextual advertising …
copyright infringement detection, product recommendation and contextual advertising …
Scalable logo recognition using proxies
I Fehérvári, S Appalaraju - 2019 IEEE Winter Conference on …, 2019 - ieeexplore.ieee.org
Logo recognition is the task of identifying and classifying logos. Logo recognition is a
challenging problem as there is no clear definition of a logo and there are huge variations of …
challenging problem as there is no clear definition of a logo and there are huge variations of …
Trajectory outlier detection: Algorithms, taxonomies, evaluation, and open challenges
Detecting abnormal trajectories is an important task in research and industrial applications,
which has attracted considerable attention in recent decades. This work studies the existing …
which has attracted considerable attention in recent decades. This work studies the existing …