The advances in remote sensing sensors during the last two decades have led to the
production of very high spatial resolution multispectral images. In order to adapt to this rapid …

Segmentation has been a rooted area of research having diverse dimensions. The roots of
image segmentation and its associated techniques have supported computer vision, pattern …

Recently, single-stage embedding based deep learning algorithms gain increasing attention
in cell segmentation and tracking. Compared with the traditional “segment-then-associate” …

Handling clustering problems are important in data statistics, pattern recognition and image
processing. The mean-shift algorithm, a common unsupervised algorithms, is widely used to …

Road networks play a fundamental role in our daily life. It is of importance to extract the road
structure in a timely and precise manner with the rapid evolution of urban road structure …

Transportation of prefabricated modules is a critical process in modular construction and can
cause additional stresses which may damage individual modules, leading to additional …

The quality and accuracy of remote sensing instruments continue to increase, allowing
geoscientists to perform various quantitative retrieval applications to observe the …

As new generations of technology appear, legacy knowledge management solutions and
applications become increasingly out of date, necessitating a paradigm shift. Machine …

Predicting computational intensity (CI) is essential for domain decomposition and load
balance in parallel geoprocessing. However, traditional CI prediction is limited in capturing …

Mean-Shift is known for its real time and robustness in visual tracking. This is a very good
algorithm. In recent years, the algorithm has developed rapidly and has great development …