Day: April 22, 2025
-
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...
-
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...
-
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...
-
Evenly Cascaded Convolutional Networks
We introduce Evenly Cascaded convolutional Network (ECN), a neural network taking in-spiration from the cascade algorithm of wavelet analysis. ECN employs two feature streams – alow-level and high-level steam. At...
-
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...
-
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...
-
Context in Human Action through Motion Complementarity
Motivated by Goldman’s Theory of Human Action – a framework in which action decomposes into 1) base physical movements, and 2) the context in which they occur – we propose...
-
Image Surveillance Assistant Architecture:Status and Planned Extensions
We are developing a system that integrates methods fromDeep Learning and AI for imagery surveillance. Ourarchitecture, the Image Surveillance Assistant (ISA), reducesthe operator burdens of info overload and fatigue by...
-
Exploring synthetic datasets for computer-aideddetection: a case study using phantom scan datafor enhanced lung nodule false positive reduction
Purpose 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...
-
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...