Search Results for author:
Found 24 papers, 1 papers with code
Exact Consistency Tests for Gaussian Mixture Filters using Normalized Deviation Squared Statistics
We consider the problem of evaluating dynamic consistency in discrete time probabilistic filters that approximate stochastic system state densities with Gaussian mixtures.
Observation-Augmented Contextual Multi-Armed Bandits for Robotic Exploration with Uncertain Semantic Data
To this end, we propose a robust Bayesian inference process for OA-CMABs that is based on the concept of probabilistic data validation.
Blind Image Quality Assessment Using Multi-Stream Architecture with Spatial and Channel Attention
BIQA (Blind Image Quality Assessment) is an important field of study that evaluates images automatically.
PIQI: Perceptual Image Quality Index based on Ensemble of Gaussian Process Regression
The scores of 0. 0552, 0. 9802 and 0. 9776 are achieved respectively for these metrics on CSIQ database.
Deep Ensembling for Perceptual Image Quality Assessment
It is demonstrated that synthetic distortion databases cannot provide generalization beyond the distortion types used in the database and they are not ideal candidates for general-purpose image quality assessment.
AAAI 2022 Fall Symposium: Lessons Learned for Autonomous Assessment of Machine Abilities (LLAAMA)
Modern civilian and military systems have created a demand for sophisticated intelligent autonomous machines capable of operating in uncertain dynamic environments.
Image Quality Assessment for Foliar Disease Identification (AgroPath)
Crop diseases are a major threat to food security and their rapid identification is important to prevent yield loss.
Active Inference for Autonomous Decision-Making with Contextual Multi-Armed Bandits
In autonomous robotic decision-making under uncertainty, the tradeoff between exploitation and exploration of available options must be considered.
Pareto Optimal Strategies for Event-Triggered Estimation
A well understood technique for trading off communication costs with estimation accuracy is event triggering (ET), where measurements are only communicated when useful, e. g., when Kalman filter innovations exceed some threshold.
A Factor-Based Framework for Decision-Making Competency Self-Assessment
We summarize our efforts to date in developing a framework for generating succinct human-understandable competency self-assessments in terms of machine self confidence, i. e. a robot's self-trust in its functional abilities to accomplish assigned tasks.
BIQ2021: A Large-Scale Blind Image Quality Assessment Database
By selecting images with naturally occurring distortions and reliable labeling, the dataset addresses the challenge of obtaining representative images for no-reference image quality assessment.
Non-Reference Quality Monitoring of Digital Images using Gradient Statistics and Feedforward Neural Networks
Assessment of the quality of images in such scenarios becomes of particular interest.
Text Mining Through Label Induction Grouping Algorithm Based Method
As LINGO uses VSM in cluster content discovery, our task is to replace VSM with LSI for cluster content discovery and to analyze the feasibility of using LSI with Okapi BM25.
HARPS: An Online POMDP Framework for Human-Assisted Robotic Planning and Sensing
Autonomous robots can benefit greatly from human-provided semantic characterizations of uncertain task environments and states.
Time Dependence in Kalman Filter Tuning
First, in theory, many of these measures do not guarantee a unique solution due to observability issues.
Development of Crop Yield Estimation Model using Soil and Environmental Parameters
The parameters collected are minimum and maximum temperature, humidity, rainfall, PH level of the soil, usage of pesticide and labor expertise.
Leaf Image-based Plant Disease Identification using Color and Texture Features
Identification of plant disease is usually done through visual inspection or during laboratory examination which causes delays resulting in yield loss by the time identification is complete.
Weak in the NEES?: Auto-tuning Kalman Filters with Bayesian Optimization
Kalman filters are routinely used for many data fusion applications including navigation, tracking, and simultaneous localization and mapping problems.
Bayesian Optimization
Simultaneous Localization and Mapping
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Optimal Continuous State POMDP Planning with Semantic Observations: A Variational Approach
This work develops novel strategies for optimal planning with semantic observations using continuous state partially observable markov decision processes (CPOMDPs).
Closed-loop Bayesian Semantic Data Fusion for Collaborative Human-Autonomy Target Search
In search applications, autonomous unmanned vehicles must be able to efficiently reacquire and localize mobile targets that can remain out of view for long periods of time in large spaces.
Data-Free/Data-Sparse Softmax Parameter Estimation with Structured Class Geometries
This note considers softmax parameter estimation when little/no labeled training data is available, but a priori information about the relative geometry of class label log-odds boundaries is available.
Adaptive Simulation-based Training of AI Decision-makers using Bayesian Optimization
This work studies how an AI-controlled dog-fighting agent with tunable decision-making parameters can learn to optimize performance against an intelligent adversary, as measured by a stochastic objective function evaluated on simulated combat engagements.
Towards Adaptive Training of Agent-based Sparring Partners for Fighter Pilots
One key benefit is that during optimization, the Gaussian Process learns a global estimate of the true objective function, with predicted outcomes and a statistical measure of confidence in areas that haven't been investigated yet.
Hybrid Repeat/Multi-point Sampling for Highly Volatile Objective Functions
With this improved model the agent is equipped to better adapt behaviors.
