Day: November 25, 2024
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Mid-Vision Feedback for Convolutional Neural Networks
Feedback plays a prominent role in biological vision, where perception is modulated based on agents’ continuous interactions with the world, and evolving expectations and world model. We introduce a novel...
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LEAP: LLM-Generation of Egocentric Action Programs
We introduce LEAP (illustrated in Figure 1), a novel method for generating video-grounded action programs through use of a Large Language Model (LLM). These action programs represent the motoric, perceptual,...
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Training CADe algorithms with synthetic datasets: augmenting clinical data for improved lung nodule detection
Synthetic datasets hold the potential to serve as cost-effective alternatives to clinical data, potentially aiding in mitigating the biases in clinical data. This paper presents a novel method that utilizes...
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Exploring synthetic datasets for computer-aided detection: a case study using phantom scan data for enhanced lung nodule false positive reduction
Synthetic datasets hold the potential to offer cost-effective alternatives to clinical data, ensuring privacy protections and potentially addressing biases in clinical data. We present a method leveraging such datasets to...
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Image Surveillance Assistant Architecture: Status and Planned Extensions
We describe our research on integrating deep learning with artificial intelligence techniques in the context of an imagery surveillance prototype designed to automatically identify imagery of interest to a user....
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Learning for action-based scene understanding
Action plays a central role in our lives and environments, yet most Computer Vision methodsdo not explicitly model action. In this chapter we outline an action-centric framework whichspans multiple time...
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Increasing the Runtime Speed of Case-Based Plan Recognition
We present PPC (Plan Projection and Clustering), an algorithm that creates a plan hierarchy for case-based plan recognition systems. PPC is motivated by a desire to improve the response time...
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Image Surveillance Assistant
Security watchstanders who monitor multiple videos over long periods of time can be susceptible to information overload and fatigue. To address this, we present a configurable perception pipeline architecture, called...
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Semi-supervised training using cooperative labeling of weakly annotated data for nodule detection in chest CT
Machine learning algorithms are best trained with large quantities of accurately annotated samples. While natural scene images can often be labeled relatively cheaply and at large scale, obtaining accurate annotations...
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A Broad Vision for Intelligent Behavior:Perpetual Real-World Cognitive Agents
We describe ongoing work toward automating human-level behavior that pulls together much oftraditional artificial intelligence in a real-time robotic setting. Natural-language dialog, planning,perception, locomotion, commonsense reasoning, memory, and learning all...