This paper presents a new 3D time-space detector for small ships in single look complex (SLC) synthetic aperture radar (SAR) imagery, optimized for small targets around 5-15 m long that are unfocused due to target motion induced by ocean surface waves.
Multi-modal data analytics publications
Deep Adaptive Semantic Logic (DASL): Compiling Declarative Knowledge into Deep Neural Networks
We introduce Deep Adaptive Semantic Logic (DASL), a novel framework for automating the generation of deep neural networks that incorporates user-provided formal knowledge to improve learning from data.
Stacked Spatio-Temporal Graph Convolutional Networks for Action Segmentation
We propose novel Stacked Spatio-Temporal Graph Convolutional Networks (Stacked-STGCN) for action segmentation, i.e., predicting and localizing a sequence of actions over long videos.
Aesop: A Visual Storytelling Platform for Conversational AI and Commonsense Grounding
We believe that the future of Artificial Intelligence (AI) will be a mixed-initiative collaboration between humans and AI as equals.
Efficient Fine-Grained Classification and Part Localization Using One Compact Network
We propose a novel multi-task deep network architecture that jointly optimizes both localization of parts and fine-grained class labels by learning from training data.
Pattern of life analysis for diverse data types
SRI has developed a system to automatically analyze the Pattern of Life of ports, routes and vessels from a large collection of AIS data. The PoL of these entities are characterized by a set of intuitive and easy to query semantic attributes.
Analyzing hyperspectral images into multiple subspaces using Gaussian mixture models
I argue that the spectra in a hyperspectral datacube will usually lie in several low-dimensional subspaces, and that these subspaces are more easily estimated from the data than the endmembers.
Sampling Exactly from the Normal Distribution
An algorithm for sampling exactly from the normal distribution is given. The algorithm reads some number of uniformly distributed random digits in a given base and generates an initial portion of the representation of a normal deviate in the same base.
Re-Ranking by Multi-Feature Fusion with Diffusion for Image Retrieval
We present a re-ranking algorithm for image retrieval by fusing multi-feature information. We utilize pairwise similarity scores between images to exploit the underlying relationships among images.