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Found 23 papers, 3 papers with code
An Index Policy Based on Sarsa and Q-learning for Heterogeneous Smart Target Tracking
Each bandit process is associated with a smart target, of which the estimation state evolves according to different discrete dynamic models for different actions - whether or not the target is being tracked.
Joint State Estimation and Noise Identification Based on Variational Optimization
In this article, the state estimation problems with unknown process noise and measurement noise covariances for both linear and nonlinear systems are considered.
Non-myopic Beam Scheduling for Multiple Smart Target Tracking in Phased Array Radar Network
We present numerical evidence that the model satisfies sufficient conditions for indexability (existence of the Whittle index) based upon partial conservation laws, and, through extensive simulations, we validate the effectiveness of the proposed policy in different scenarios.
Classification-Aided Robust Multiple Target Tracking Using Neural Enhanced Message Passing
We first introduce a novel neural enhanced message passing approach, where the beliefs obtained by the unified message passing are fed into the neural network as additional information.
Exploring Part-Informed Visual-Language Learning for Person Re-Identification
Recently, visual-language learning has shown great potential in enhancing visual-based person re-identification (ReID).
Combinatorial-restless-bandit-based Transmitter-Receiver Online Selection for Distributed MIMO Radars With Non-Stationary Channels
We track moving targets with a distributed multiple-input multiple-output (MIMO) radar, for which the transmitters and receivers are appropriately paired and selected with a limited number of radar stations.
Variational Nonlinear Kalman Filtering with Unknown Process Noise Covariance
Motivated by the maneuvering target tracking with sensors such as radar and sonar, this paper considers the joint and recursive estimation of the dynamic state and the time-varying process noise covariance in nonlinear state space models.
A Sea-Land Clutter Classification Framework for Over-the-Horizon-Radar Based on Weighted Loss Semi-supervised GAN
The semi-supervised classification performance of WL-SSGAN is evaluated on a sea-land clutter dataset.
Data Augmentation and Classification of Sea-Land Clutter for Over-the-Horizon Radar Using AC-VAEGAN
Using a dataset of OTHR sea-land clutter, both the quality of the synthetic samples and the performance of data augmentation of AC-VAEGAN are verified.
Robust Multitarget Tracking in Interference Environments: A Message-Passing Approach
Then, a unified MP algorithm is used to infer the marginal posterior probability distributions of targets, clutter, and data association by splitting the joint probability distribution into a mean-field approximate part and a belief propagation part.
Crowd counting with segmentation attention convolutional neural network
With the guidance of an attention mechanism, the proposed SegCrowdNet pays more attention to the human head region and automatically encodes the highly refined density map.
SSR-HEF: Crowd Counting with Multi-Scale Semantic Refining and Hard Example Focusing
Existing methods with simple Euclidean distance algorithm indiscriminately optimize the hard and easy examples so that the densities of hard examples are usually incorrectly predicted to be lower or even zero, which results in large counting errors.
Crowd counting with crowd attention convolutional neural network
Crowd counting is a challenging problem due to the scene complexity and scale variation.
Submarine Cable Network Design for Regional Connectivity
It differs from the Euclidean Steiner tree problem, where Steiner points are forced to have degree three; this is no longer the case, in general, when nodes incur a cost.
On Exploring and Improving Robustness of Scene Text Detection Models
It is crucial to understand the robustness of text detection models with regard to extensive corruptions, since scene text detection techniques have many practical applications.
Greedy Offset-Guided Keypoint Grouping for Human Pose Estimation
Given an image, we employ an Hourglass Network to infer all the keypoints from different persons indiscriminately as well as the guiding offsets connecting the adjacent keypoints belonging to the same persons.
Ranked #10 on
Pose Estimation
on CrowdPose
Optimal Tree Topology for a Submarine Cable Network With Constrained Internodal Latency
For cable systems for which ILP is not able to find the optimal solution within an acceptable time, we propose an alternative heuristic algorithm based on Prim's algorithm.
OTHR multitarget tracking with a GMRF model of ionospheric parameters
Therefore, to improve the localization accuracy of OTHR, it is important to develop accurate models and estimation methods of ionospheric parameters and the corresponding target tracking algorithms.
Simple Pose: Rethinking and Improving a Bottom-up Approach for Multi-Person Pose Estimation
We rethink a well-know bottom-up approach for multi-person pose estimation and propose an improved one.
Ranked #9 on
Keypoint Detection
on COCO test-dev
Grand Challenge of 106-Point Facial Landmark Localization
However, previous competitions on facial landmark localization (i. e., the 300-W, 300-VW and Menpo challenges) aim to predict 68-point landmarks, which are incompetent to depict the structure of facial components.
Joint Target Detection and Tracking in Multipath Environment: A Variational Bayesian Approach
We consider multitarget detection and tracking problem for a class of multipath detection system where one target may generate multiple measurements via multiple propagation paths, and the association relationship among targets, measurements and propagation paths is unknown.
Nighttime Haze Removal with Illumination Correction
ii) Then it achieves a color-balance result by performing a color correction step after estimating the color characteristics of the incident light.
