Selecting influential examples: Active learning with expected model output changes
In this paper, we introduce a new general strategy for active learning. The key idea of our
approach is to measure the expected change of model outputs, a concept that generalizes …
approach is to measure the expected change of model outputs, a concept that generalizes …
One-class classification with gaussian processes
Detecting instances of unknown categories is an important task for a multitude of problems
such as object recognition, event detection, and defect localization. This article investigates …
such as object recognition, event detection, and defect localization. This article investigates …
Local novelty detection in multi-class recognition problems
In this paper, we propose using local learning for multiclass novelty detection, a framework
that we call local novelty detection. Estimating the novelty of a new sample is an extremely …
that we call local novelty detection. Estimating the novelty of a new sample is an extremely …
Active learning and discovery of object categories in the presence of unnameable instances
Current visual recognition algorithms are" hungry" for data but massive annotation is
extremely costly. Therefore, active learning algorithms are required that reduce labeling …
extremely costly. Therefore, active learning algorithms are required that reduce labeling …
Change detection using high resolution remote sensing images based on active learning and Markov random fields
Change detection has been widely used in remote sensing, such as for disaster assessment
and urban expansion detection. Although it is convenient to use unsupervised methods to …
and urban expansion detection. Although it is convenient to use unsupervised methods to …
GPU optimization of the SGM stereo algorithm
I Haller, S Nedevschi - Proceedings of the 2010 IEEE 6th …, 2010 - ieeexplore.ieee.org
GPU hardware architectures have evolved into a suitable platform for the hardware
acceleration of complex computing tasks. Stereo vision is one such task where acceleration …
acceleration of complex computing tasks. Stereo vision is one such task where acceleration …
Active online anomaly detection using dirichlet process mixture model and gaussian process classification
We present a novel anomaly detection (AD) system for streaming videos. Different from prior
methods that rely on unsupervised learning of clip representations, that are usually coarse in …
methods that rely on unsupervised learning of clip representations, that are usually coarse in …
Gaussian process for predicting CPU utilization and its application to energy efficiency
For the past ten years, Gaussian process has become increasingly popular for modeling
numerous inferences and reasoning solutions due to the robustness and dynamic features …
numerous inferences and reasoning solutions due to the robustness and dynamic features …
Temporal self-similarity for appearance-based action recognition in multi-view setups
We present a general data-driven method for multi-view action recognition relying on the
appearance of dynamic systems captured from different viewpoints. Thus, we do not depend …
appearance of dynamic systems captured from different viewpoints. Thus, we do not depend …
Decoding affect in videos employing the MEG brain signal
This paper presents characterization of affect (valence and arousal) using the
Magnetoencephalogram (MEG) brain signal. We attempt single-trial classification of movie …
Magnetoencephalogram (MEG) brain signal. We attempt single-trial classification of movie …