In recent years, crowd counting has attracted widespread attention due to its enormous
potential in the public safety inspection process. Visual-based measurement techniques …

The new shoot density of slash pine serves as a vital indicator for assessing its growth and
photosynthetic capacity, while the number of new shoots offers an intuitive reflection of this …

Currently, existing semi-supervised crowd counting methods usually learn unlabeled
images through pseudo-labels and spatial consistency regularization paradigm. However …

Few-shot object counting (FSOC) estimates object quantities in query images using a few of
support information. Unlike traditional counting methods, FSOC prioritizes more …

Existing crowd counting methods generally focus on addressing variations in crowd size,
density, and distribution, often overlooking the challenges posed by low-resolution (LR) …

Accurate assessment of high-density underwater fish resources is vital to the aquaculture
industry. It is directly related to the formulation of fishery insurance strategies and the …

Unsupervised domain adaptive vehicle density estimation aims to transfer the knowledge
learned from the labeled source domain to the unlabeled target domain, which has received …

In order to solve the problem of weak single domain generalization ability in existing crowd
counting methods, this study proposes a new crowd counting framework called Multi-scale …

In a crowd density estimation dataset, the annotation of crowd locations is an extremely
laborious task, and they are not taken into the evaluation metrics. In this paper, we aim to …

Automated crowd counting has emerged as a vision-based measurement method for crowd
analysis and management. However, current methods based on density maps still suffer …