Visual categorization problems, such as object classification or action recognition,
are increasingly often approached using a detection strategy: a classifier function
is first ...
Minh Hoai Nguyen, Lorenzo Torresani, Fernando de l...
We present a method for unsupervised discovery of abnormal occurrences of activities in multi-dimensional time series data. Unsupervised activity discovery approaches differ from ...
Abstract. This paper presents an exemplar-based approach to detecting and localizing human actions, such as running, cycling, and swinging, in realistic videos with dynamic backgro...
— The paper proposes a hypernetwork-based method for stock market prediction through a binary time series problem. Hypernetworks are a random hypergraph structure of higher-order...
Elena Bautu, Sun Kim, Andrei Bautu, Henri Luchian,...
Novelty detection in time series is an important problem with application in different domains such as machine failure detection, fraud detection and auditing. An approach to this...
Adriano L. I. Oliveira, Fernando Buarque de Lima N...