It is a feasible and promising way to utilize deep neural networks to learn and extract valuable
features from synthetic aperture radar (SAR) images for SAR automatic target recognition (…

Ship target detection using large-scale synthetic aperture radar (SAR) images has important
application in military and civilian fields. However, ship targets are difficult to distinguish …

Recent transformer-based solutions have been introduced to estimate 3D human pose from
2D keypoint sequence by considering body joints among all frames globally to learn spatio-…

Firstly, this paper analyzes the basic principles and processes of the spatial pattern changes
of land use in towns and villages, and the result shows that the land resource demands of …

Causal inference in complex systems has been largely promoted by the proposal of some
advanced temporal causation models. However, temporal models have serious limitations …

Electro-coagulation-flotation (ECF) is one of the most promising technologies that offers an
attractive alternative to conventional coagulation and flotation. In this study, the effectiveness …

This study proposes a novel non‐negative matrix factorisation (NMF) variant L 1/2 ‐NMF
after visualisation and analysis of the process of target recognition via NMF for synthetic …

This paper considers the multi-target tracking (MTT) problem through the use of dynamic
programming based track-before-detect (DP-TBD) methods. The usual solution of this problem …

With appropriate geometry configurations, bistatic synthetic aperture radar (SAR) can break
through the limitations of monostatic SAR on forward-looking imaging. Thanks to such a …

Grid technology is now being increasingly applied in the process of remotely sensed images
due to its characteristics, including distribution, high performance, dynamics, extendability …