Recent advances of single-object tracking methods: A brief survey
Single-object tracking is regarded as a challenging task in computer vision, especially in
complex spatio-temporal contexts. The changes in the environment and object deformation …
complex spatio-temporal contexts. The changes in the environment and object deformation …
Multi-regularized correlation filter for UAV tracking and self-localization
As a sort of model-free tracking approach, discriminative correlation filter (DCF)-based
trackers have shown prominent performance in unmanned aerial vehicle (UAV) tracking …
trackers have shown prominent performance in unmanned aerial vehicle (UAV) tracking …
A vehicle detection and tracking method for traffic video based on faster R-CNN
M Othmani - Multimedia Tools and Applications, 2022 - Springer
In this paper we present a vehicle detection and tracking method for traffic video analysis
based on deep learning technology. Indeed, with the rapid development of deep neural …
based on deep learning technology. Indeed, with the rapid development of deep neural …
Smalltrack: Wavelet pooling and graph enhanced classification for uav small object tracking
Y Xue, G Jin, T Shen, L Tan, N Wang… - … on Geoscience and …, 2023 - ieeexplore.ieee.org
Aerial object tracking has recently shown great potential in the field of remote sensing.
However, small objects with limited feature information pose a huge challenge to aerial …
However, small objects with limited feature information pose a huge challenge to aerial …
Classification of retinal images based on convolutional neural network
Automatic detection of maculopathy disease is a very important step to achieve high‐
accuracy results for the early discovery of the disease to help ophthalmologists to treat …
accuracy results for the early discovery of the disease to help ophthalmologists to treat …
A review of three dimensional reconstruction techniques
Three dimensional (3D) modeling is an important stereoscopic representation of an object
for multiple viewpoints aggregation and geometrical information. A general 3D modeling …
for multiple viewpoints aggregation and geometrical information. A general 3D modeling …
Memory network with pixel-level spatio-temporal learning for visual object tracking
Making full use of temporal and spatial information is critical to cope with the appearance
changes of objects in visual object tracking. However, existing methods in the tracking field …
changes of objects in visual object tracking. However, existing methods in the tracking field …
Object tracking via spatial-temporal memory network
Temporal and spatial contexts, characterizing target appearance variations and target-
background differences, respectively, are crucial for improving the online adaptive ability …
background differences, respectively, are crucial for improving the online adaptive ability …
An anchor-free network with density map and attention mechanism for multiscale object detection in aerial images
Accurate detection of the multiple classes in aerial images has become possible with the
use of anchor-based object detectors. However, anchor-based object detectors place a …
use of anchor-based object detectors. However, anchor-based object detectors place a …
Hourly prediction of PM2.5 concentration in Beijing based on Bi-LSTM neural network
M Zhang, D Wu, R Xue - Multimedia Tools and Applications, 2021 - Springer
The concentration of PM 2.5 is closely related to air, environmental quality and human
health. In this study, an hourly prediction method of PM 2.5 concentration in Beijing based …
health. In this study, an hourly prediction method of PM 2.5 concentration in Beijing based …