Search Results for author:
Found 11 papers, 4 papers with code
Robust Divergence Angle for Inter-satellite Laser Communications under Target Deviation Uncertainty
Simulation results show the approach leads to significantly more robust performance than using the divergence angle as if there is no deviation, or other ad-hoc schemes.
Active Learning for Deep Visual Tracking
In this paper, we propose an active learning method for deep visual tracking, which selects and annotates the unlabeled samples to train the deep CNNs model.
SiamCorners: Siamese Corner Networks for Visual Tracking
By tracking a target as a pair of corners, we avoid the need to design the anchor boxes.
Efficient Medical Image Segmentation with Intermediate Supervision Mechanism
However, U-Net is mainly engaged in segmentation, and the extracted features are also targeted at segmentation location information, and the input and output are different.
Robot Trajectory Planning With QoS Constrained IRS-assisted Millimeter-Wave Communications
We present a solution to the optimization problem that exploits mm-wave channel characteristics to decouple beamforming and trajectory optimizations.
Trajectory Planning
Networking and Internet Architecture
LSOTB-TIR:A Large-Scale High-Diversity Thermal Infrared Object Tracking Benchmark
We evaluate and analyze more than 30 trackers on LSOTB-TIR to provide a series of baselines, and the results show that deep trackers achieve promising performance.
Thermal Infrared Object Tracking
Vocal Bursts Intensity Prediction
Accurate Bounding-box Regression with Distance-IoU Loss for Visual Tracking
Moreover, we introduce a classification part that is trained online and optimized with a Conjugate-Gradient-based strategy to guarantee real-time tracking speed.
Learning-Based Link Scheduling in Millimeter-wave Multi-connectivity Scenarios
Multi-connectivity is emerging as a promising solution to provide reliable communications and seamless connectivity for the millimeter-wave frequency range.
Multi-Task Driven Feature Models for Thermal Infrared Tracking
These two feature models are learned using a multi-task matching framework and are jointly optimized on the TIR tracking task.
Learning Deep Multi-Level Similarity for Thermal Infrared Object Tracking
These two similarities complement each other and hence enhance the discriminative capacity of the network for handling distractors.
Particle filter re-detection for visual tracking via correlation filters
Most of the correlation filter based tracking algorithms can achieve good performance and maintain fast computational speed.
