21 citations · 25 across the 9 of their papers we have counts for
9 papers
Deep learning for echo sounder data
Ketil Malde
There is no doubt that over the last decade, techniques from the field of machine learning have revolutionized how we process and interpret data, especially images and text. For un…
YASMOT: Yet another stereo image multi-object tracker
Ketil Malde
There now exists many popular object detectors based on deep learning that can analyze images and extract locations and class labels for occurrences of objects. For image time seri…
Inspecting class hierarchies in classification-based metric learning models
Hyeongji Kim, Pekka Parviainen, Terje Berge +1
Most classification models treat all misclassifications equally. However, different classes may be related, and these hierarchical relationships must be considered in some classifi…
A contrastive learning approach for individual re-identification in a wild fish population
Ørjan Langøy Olsen, Tonje Knutsen Sørdalen, Morten Goodwin +3
In both terrestrial and marine ecology, physical tagging is a frequently used method to study population dynamics and behavior. However, such tagging techniques are increasingly be…
Distance-Ratio-Based Formulation for Metric Learning
Hyeongji Kim, Pekka Parviainen, Ketil Malde
In metric learning, the goal is to learn an embedding so that data points with the same class are close to each other and data points with different classes are far apart. We propo…
Measuring Adversarial Robustness using a Voronoi-Epsilon Adversary
Hyeongji Kim, Pekka Parviainen, Ketil Malde
Previous studies on robustness have argued that there is a tradeoff between accuracy and adversarial accuracy. The tradeoff can be inevitable even when we neglect generalization. W…