Simultaneous retrieval of selected optical water quality indicators from Landsat-8, Sentinel-2, and Sentinel-3
Constructing multi-source satellite-derived water quality (WQ) products in inland and
nearshore coastal waters from the past, present, and future missions is a long-standing …
nearshore coastal waters from the past, present, and future missions is a long-standing …
Generating multiple hypotheses for 3d human pose estimation with mixture density network
Abstract 3D human pose estimation from a monocular image or 2D joints is an ill-posed
problem because of depth ambiguity and occluded joints. We argue that 3D human pose …
problem because of depth ambiguity and occluded joints. We argue that 3D human pose …
[PDF][PDF] A Survey on Uncertainty Quantification Methods for Deep Learning
A Survey on Uncertainty Quantification Methods for Deep Neural Networks: An Uncertainty
Source's Perspective Page 1 A Survey on Uncertainty Quantification Methods for Deep Neural …
Source's Perspective Page 1 A Survey on Uncertainty Quantification Methods for Deep Neural …
Likelihood approximation networks (LANs) for fast inference of simulation models in cognitive neuroscience
In cognitive neuroscience, computational modeling can formally adjudicate between
theories and affords quantitative fits to behavioral/brain data. Pragmatically, however, the …
theories and affords quantitative fits to behavioral/brain data. Pragmatically, however, the …
Uncertainty quantification of a deep learning model for failure rate prediction of water distribution networks
Predicting the time-dependent pipe failure rate of the water distribution networks (WDNs) is
important for planning its renewal budget but also challenging due to the complex factors …
important for planning its renewal budget but also challenging due to the complex factors …
Uncertainty-aware learning from demonstration using mixture density networks with sampling-free variance modeling
In this paper, we propose an uncertainty-aware learning from demonstration method by
presenting a novel uncertainty estimation method utilizing a mixture density network …
presenting a novel uncertainty estimation method utilizing a mixture density network …
[HTML][HTML] XAS: Automatic yet explainable age and sex determination by combining imprecise per-tooth predictions
N Vila-Blanco, P Varas-Quintana… - Computers in Biology …, 2022 - Elsevier
Chronological age and biological sex estimation are two key tasks in a variety of
procedures, including human identification and migration control. Issues such as these have …
procedures, including human identification and migration control. Issues such as these have …
A hyperspectral inversion framework for estimating absorbing inherent optical properties and biogeochemical parameters in inland and coastal waters
The simultaneous remote estimation of biogeochemical parameters (BPs) and inherent
optical properties (IOPs) from hyperspectral satellite imagery of globally distributed optically …
optical properties (IOPs) from hyperspectral satellite imagery of globally distributed optically …
Attention-based multitask probabilistic network for nonintrusive appliance load monitoring
S Dash, NC Sahoo - IEEE Transactions on Instrumentation and …, 2023 - ieeexplore.ieee.org
Monitoring individual appliances' operating state and energy consumption in a building
enables significant energy-saving opportunities. These days, smart meters perform this task …
enables significant energy-saving opportunities. These days, smart meters perform this task …
Performance modeling a near-infrared tof lidar under fog: A data-driven approach
As a critical sensor for high-level autonomous vehicles, LiDAR's limitations in adverse
weather (eg rain, fog, snow, etc.) impede the deployment of self-driving cars in all weather …
weather (eg rain, fog, snow, etc.) impede the deployment of self-driving cars in all weather …