Nov 14, 2023 · In this paper, we propose a multi-task cell recognition framework. The framework utilizes a regression task to adaptively generate smooth pseudo labels with ...
Nov 20, 2023 · In this paper, we propose a multi-task cell recognition framework. The framework utilizes a regression task to adaptively generate smooth pseudo labels.
Using point annotations for weakly supervised learning is a common approach for cell recognition, which significantly reduces the labeling workload. Cell ...
Adaptive Focal Inverse Distance Transform Maps for Cell Recognition ... Authors: Wenjie Huang; Xing Wu; Chengliang Wang; Zailin Yang; Longrong Ran; Yao Liu. List ...
Adaptive Focal Inverse Distance Transform Maps for Cell Recognition. W. Huang, X. Wu, C. Wang, Z. Yang, L. Ran, and Y. Liu. ICONIP (6), volume 14452 of ...
In this paper, we focus on the crowd localization task, a crucial topic of crowd analysis. Most regression-based methods utilize convolution neural networks ...
We propose a novel Focal Inverse Distance Transform (FIDT) map for the crowd localization task. Compared with the density maps, the FIDT maps accurately ...
Missing: Adaptive Cell
Rapidly Adaptive Cell Detection Using Transfer Learning with a Global ...
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Learning-based cell detectors tend to be specific to a particular imaging protocol and cell type. For a new dataset, a tedious re-training process is required.
Oct 22, 2024 · The proposed approach integrates a deep learning model that produces an inverse distance transform-based detection map from the given image, ...
The recently proposed Focal Inverse Distance Transform Maps primarily utilize CNNs to generate basic density maps for crowd size estimation but typically ...