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Found 9 papers, 1 papers with code
Feature Alignment: Rethinking Efficient Active Learning via Proxy in the Context of Pre-trained Models
Fine-tuning the pre-trained model with active learning holds promise for reducing annotation costs.
NTKCPL: Active Learning on Top of Self-Supervised Model by Estimating True Coverage
Recent research has shown that in the context of supervised learning different active learning strategies need to be applied at various stages of the training process to ensure improved performance over the random baseline.
A Semi-supervised Object Detection Algorithm for Underwater Imagery
We evaluate the precision-recall tradeoff and demonstrate that by choosing an appropriate latent dimensionality and threshold, we are able to achieve an average precision of 0. 64 on unlabelled datasets.
Improved Benthic Classification using Resolution Scaling and SymmNet Unsupervised Domain Adaptation
We adapt the SymmNet state-of-the-art Unsupervised Domain Adaptation method with an efficient bilinear pooling layer and image scaling to normalise spatial resolution, and show improved classification accuracy.
Training from a Better Start Point: Active Self-Semi-Supervised Learning for Few Labeled Samples
Consequently, our framework can significantly improve the performance of models in the case of few annotations while reducing the training time.
GeoCLR: Georeference Contrastive Learning for Efficient Seafloor Image Interpretation
We demonstrate how the latent representations generated by GeoCLR can be used to efficiently guide human annotation efforts, where the semi-supervised framework improves classification accuracy by an average of 10. 2% compared to the state-of-the-art SimCLR using the same CNN and equivalent number of human annotations for training.
Feature Space Exploration For Planning Initial Benthic AUV Surveys
This research proposes methods for planning initial AUV surveys that efficiently explore a feature space representation of the bathymetry, in order to sample from a diverse set of bathymetric terrain.
Towards Adaptive Benthic Habitat Mapping
One such application is in benthic habitat mapping where these vehicles collect seafloor imagery that complements broadscale bathymetric data collected using sonar.
Decoding, Calibration and Rectification for Lenselet-Based Plenoptic Cameras
Results include calibration of a commercially available camera using three calibration grid sizes over five datasets.
