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Found 8 papers, 1 papers with code
Leveraging Tacit Information Embedded in CNN Layers for Visual Tracking
Different layers in CNNs provide not only different levels of abstraction for describing the objects in the input but also encode various implicit information about them.
UNI-EM: An Environment for Deep Neural Network-Based Automated Segmentation of Neuronal Electron Microscopic Images
The spatial scale of the 3D reconstruction grows rapidly owing to deep neural networks (DNNs) that enable automated image segmentation.
Long and Short Memory Balancing in Visual Co-Tracking using Q-Learning
Employing one or more additional classifiers to break the self-learning loop in tracing-by-detection has gained considerable attention.
Information-Maximizing Sampling to Promote Tracking-by-Detection
We introduced the idea of most informative sampling, in which the sampler attempts to select samples that trouble the classifier of a discriminative tracker.
Efficient Diverse Ensemble for Discriminative Co-Tracking
To remove this redundancy and have an effective ensemble learning, it is critical for the committee to include consistent hypotheses that differ from one-another, covering the version space with minimum overlaps.
Active Collaborative Ensemble Tracking
However, by updating all of the ensemble using a shared set of samples and their final labels, such diversity is lost or reduced to the diversity provided by the underlying features or internal classifiers' dynamics.
Efficient Version-Space Reduction for Visual Tracking
To cope with variations of the target shape and appearance, the classifier is updated online with different samples of the target and the background.
Efficient Asymmetric Co-Tracking using Uncertainty Sampling
We also introduce a budgeting mechanism which prevents the unbounded growth in the number of examples in the first detector to maintain its rapid response.
