We develop Augmented Intelligence algorithms for our software products and embedded hardware integration. Our technologies include automated target recognition, multi-sensor fusion, natural language processing of social media data, and super-resolution image enhancement.

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Online Random Forest for Automatic SAR Image Segmentation

Online Random Forest for Automatic SAR Image Segmentation (ORFASIS) is a computer vision system that provides automatic, pixel-level, highly accurate terrain type segmentation of synthetic aperture radar (SAR) imagery to reduce analyst workload and streamline additional analyses.

Binarized Deep Fusion Classification

Our Binarized Deep Fusion Classification (BDFC) algorithm provides multi-sensor fusion using artificial neural networks (ANN) for ship classification. Binarization of the network weights reduces memory constraints and has been shown to increase the solution rate by up to thirty percent.

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Efficient Multi-Sensor Fusion via Artificial Intelligence

The Efficient Multi-Sensor Fusion via Artificial Intelligence (EMulSeFAI) system features our compact deep learning model which fuses multimodal inputs from acoustic, magnetic, and seismic sensors to achieve highly accurate object classification and detection with a very low false alarm rate.

Assistive Compact Convolutional Enhanced Neural Targeting

By taking in real-time color or thermal motion imagery, Assistive Compact Convolutional Enhanced Neural Targeting (ACCENT) automatically improves the contrast, acuity, and stability of imagery to provide perceptual enhancement to the user.

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Deep Learning for Infrared Video Pedestrian Recognition

Our Deep Learning for Infrared Video Pedestrian Recognition (DELIVER) system utilizes convolutional neural network algorithms for automatic object detection, classification, and localization of humans in infrared video.

Interested In Learning More

Whether you are a supplier, customer, potential employee, journalist, or investor that wants to learn more about Intellisense Systems, Inc., please call us at 310.320.1827 or fill out the information form and we will contact you.