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Crowd Size Estimation: Smart Gathering Management
Linear increase in population which results in overcrowding has become an unavoidable element in any public gathering. Public safety under such...
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A data-driven approach for high accurate spatiotemporal precipitation estimation
Precipitation is a fundamental factor affecting many fields, including freshwater reservation, flood warning and prevention, agriculture, and...
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Fast Estimation of Multidimensional Regression Functions by the Parzen Kernel-Based Method
Various methods for estimation of unknown functions from the set of noisy measurements are applicable to a wide variety of problems. Among them the...
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Cardinality estimation using normalizing flow
Cardinality estimation is one of the most important problems in query optimization. Recently, machine learning-based techniques have been proposed to...
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Doubly robust estimation and robust empirical likelihood in generalized linear models with missing responses
In this paper, we study doubly robust estimation and robust empirical likelihood of regression parameter for generalized linear models with missing...
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A density estimation approach for detecting and explaining exceptional values in categorical data
In this work we deal with the problem of detecting and explaining anomalous values in categorical datasets. We take the perspective of perceiving an...
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Robust primary quantization step estimation on resized and double JPEG compressed images
As one of the most important forensic tasks, reconstruction of the original information in tampered images is a key step for tampering detection and...
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Airport Boarding Bridge Pedestrian Detection Based on Spatial Attention and Joint Crowd Density Estimation
Pedestrian detection serves as the cornerstone of pedestrian tracking and re-identification, playing a pivotal role in the realm of intelligent...
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Robust point cloud normal estimation via multi-level critical point aggregation
We propose a multi-level critical point aggregation architecture based on a graph attention mechanism for 3D point cloud normal estimation, which can...
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On Strong Basins of Attractions for Non-convex Sparse Spike Estimation: Upper and Lower Bounds
In this article, we study the size of strong basins of attractions for the non-convex sparse spike estimation problem. We first extend previous...
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Structure guided network for human pose estimation
Humans have an impressive ability to reliably perceive pose with semantic descriptions (e.g. both arm up or left leg bent). To leverage the...
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DepthFormer: Exploiting Long-range Correlation and Local Information for Accurate Monocular Depth Estimation
This paper aims to address the problem of supervised monocular depth estimation. We start with a meticulous pilot study to demonstrate that the...
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Automatic multi-view registration of point clouds via a high-quality descriptor and a novel 3D transformation estimation technique
Generally, performing multiple scans is necessary to cover entire scanning area, and multiple point clouds are thus obtained. These point clouds need...
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A Stochastic-Geometrical Framework for Object Pose Estimation Based on Mixture Models Avoiding the Correspondence Problem
Pose estimation of rigid objects is a practical challenge in optical metrology and computer vision. This paper presents a novel...
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VTP: volumetric transformer for multi-view multi-person 3D pose estimation
This paper presents Volumetric Transformer Pose Estimator (VTP), the first 3D volumetric transformer framework for multi-view multi-person 3D human...
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Uncertainty estimation based adversarial attack in multi-class classification
Model uncertainty has gained popularity in machine learning due to the overconfident predictions derived from standard neural networks which are not...
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Empirical likelihood and estimation in single-index varying-coefficient models with censored data
In this paper, we study the empirical likelihood and estimation of parameters of interest in single-index varying coefficient models with right...
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Polya tree-based nearest neighborhood regression
Parametric regression, such as linear regression, plays an important role in statistics. The use of parametric regression models typically involves...
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A review of predictive uncertainty estimation with machine learning
Predictions and forecasts of machine learning models should take the form of probability distributions, aiming to increase the quantity of...
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Lightweight head pose estimation without keypoints based on multi-scale lightweight neural network
Head pose estimation methods without facial key points have emerged as a promising research field. However, there remain several unsolved challenges....
