24 citations · 41 across the 8 of their papers we have counts for
9 papers · 1 filter
Iterative, Deep Synthetic Aperture Sonar Image Segmentation
Yung-Chen Sun, Isaac D. Gerg, Vishal Monga
Synthetic aperture sonar (SAS) systems produce high-resolution images of the seabed environment. Moreover, deep learning has demonstrated superior ability in finding robust feature…
Iterative, Deep, and Unsupervised Synthetic Aperture Sonar Image Segmentation
Yung-Chen Sun, Isaac D. Gerg, Vishal Monga
Deep learning has not been routinely employed for semantic segmentation of seabed environment for synthetic aperture sonar (SAS) imagery due to the implicit need of abundant traini…
Real-Time, Deep Synthetic Aperture Sonar (SAS) Autofocus
Isaac D. Gerg, Vishal Monga
Synthetic aperture sonar (SAS) requires precise time-of-flight measurements of the transmitted/received waveform to produce well-focused imagery. It is not uncommon for errors in t…
Structural Prior Driven Regularized Deep Learning for Sonar Image Classification
Isaac D. Gerg, Vishal Monga
Deep learning has been recently shown to improve performance in the domain of synthetic aperture sonar (SAS) image classification. Given the constant resolution with range of a SAS…
Measuring Human Assessed Complexity in Synthetic Aperture Sonar Imagery Using the Elo Rating System
Brian Reinhardt, Isaac Gerg, Daniel Brown +1
Performance of automatic target recognition from synthetic aperture sonar data is heavily dependent on the complexity of the beamformed imagery. Several mechanisms can contribute t…
Multiband SAS Imagery
Isaac D Gerg
Advances in unmanned synthetic aperture sonar (SAS) imaging platforms allow for the simultaneous collection of multiband SAS imagery. The imagery is collected over several octaves…
Additional Representations for Improving Synthetic Aperture Sonar Classification Using Convolutional Neural Networks
Isaac Gerg, David Williams
Object classification in synthetic aperture sonar (SAS) imagery is usually a data starved and class imbalanced problem. There are few objects of interest present among much benign…
Bridging the Gap: Simultaneous Fine Tuning for Data Re-Balancing
John McKay, Isaac Gerg, Vishal Monga
There are many real-world classification problems wherein the issue of data imbalance (the case when a data set contains substantially more samples for one/many classes than the re…
What's Mine is Yours: Pretrained CNNs for Limited Training Sonar ATR
John McKay, Isaac Gerg, Vishal Monga +1
Finding mines in Sonar imagery is a significant problem with a great deal of relevance for seafaring military and commercial endeavors. Unfortunately, the lack of enormous Sonar im…