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Home » Publication » Computer vision publications » Machine learning publications

Machine learning publications

Machine learning publications June 20, 2023

C-SFDA: A Curriculum Learning Aided Self-Training Framework for Efficient Source Free Domain Adaptation

Supun Samarasekera, Han-Pang Chiu

We propose C-SFDA, a curriculum learning aided self-training framework for SFDA that adapts efficiently and reliably to changes across domains based on selective pseudo-labeling. Specifically, we employ a curriculum learning scheme to promote learning from a restricted amount of pseudo labels selected based on their reliabilities.

Machine learning publications March 27, 2023

Night-Time GPS-Denied Navigation and Situational Understanding Using Vision-Enhanced Low-Light Imager

Han-Pang Chiu, Supun Samarasekera, Rakesh Kumar

In this presentation, we describe and demonstrate a novel vision-enhanced low-light imager system to provide GPS-denied navigation and ML-based visual scene understanding capabilities for both day and night operations.

2d-3d reasoning and augmented reality publications March 25, 2023

Cross-View Visual Geo-Localization for Outdoor Augmented Reality

Han-Pang Chiu, Supun Samarasekera, Rakesh Kumar

We address the problem of geo-pose estimation by cross-view matching of query ground images to a geo-referenced aerial satellite image database. Recently, neural network-based methods have shown state-of-the-art performance in cross-view matching.

Artificial intelligence publications November 3, 2022

Sensor Control for Information Gain in Dynamic, Sparse and Partially Observed Environments

Aravind Sundaresan, Pedro Sequeira, Vidyasagar Sadhu

We present an approach for autonomous sensor control for information gathering under partially observable, dynamic and sparsely sampled environments.

Machine learning publications September 21, 2022

Unpacking Large Language Models with Conceptual Consistency

SRI International

We propose conceptual consistency to measure a LLM’s understanding of relevant concepts. This novel metric measures how well a model can be characterized by finding out how consistent its responses to queries about conceptually relevant background knowledge are.

Machine learning publications July 14, 2022

Incremental Learning with Differentiable Architecture and Forgetting Search

Han-Pang Chiu

In this paper, we show that leveraging NAS for incremental learning results in strong performance gains for classification tasks.

Machine learning publications July 10, 2022

Dual-Key Multimodal Backdoors for Visual Question Answering

SRI International

In this work, we show that multimodal networks are vulnerable to a novel type of attack that we refer to as Dual-Key Multimodal Backdoors.

Machine learning publications June 19, 2022

Saccade Mechanisms for Image Classification, Object Detection and Tracking

David Zhang

We examine how the saccade mechanism from biological vision can be used to make deep neural networks more efficient for classification and object detection problems.

Machine learning publications June 8, 2022

Conformal Prediction Intervals for Markov Decision Process Trajectories

Jesse Hostetler

This paper extends previous work on conformal prediction for functional data and conformalized quantile regression to provide conformal prediction intervals over the future behavior of an autonomous system executing a fixed control policy on a Markov Decision Process.

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