Results 71 to 80 of about 16,201 (241)
Remote Sensing, 2022 The discrepancies in existing land cover data are relatively high, indicating low local precision and application limitations. Multisource data fusion is an effective way to solve this problem; however, the fusion procedure often requires resampling to ...
Qi Jin, Erqi Xu, Xuqing Zhang
doaj +1 more source
How good are detection proposals, really?
, 2014 Current top performing Pascal VOC object detectors employ detection proposals to guide the search for objects thereby avoiding exhaustive sliding window search across images.
Benenson, Rodrigo +2 more
core +1 more source
Small, EarlyView.This study presents an interpretable, lightweight hybrid deep learning model for real‐time analysis of breast cancer histopathology in IoMT‐enabled diagnostic systems. By integrating MobileNetV2 and EfficientNet‐B0 with a novel contextual recurrent attention module (CRAM), the framework achieves near‐perfect accuracy while providing transparent Grad ...
Roseline Oluwaseun Ogundokun +4 more
wiley +1 more source
A deep learning‐enabled toolkit for the 3D segmentation of ventricular cardiomyocytes
The Journal of Physiology, EarlyView.Abstract figure legend 3D cardiomyocyte segmentation enables comprehensive analyses of myocardial microstructure in health and disease; however, it is technically demanding. We present an open‐source toolkit for this task, which reduces challenges associated with sample preparation, image restoration, segmentation and proofreading.
Joachim Greiner +6 more
wiley +1 more source
Geodesic Distance Histogram Feature for Video Segmentation
, 2017 This paper proposes a geodesic-distance-based feature that encodes global information for improved video segmentation algorithms. The feature is a joint histogram of intensity and geodesic distances, where the geodesic distances are computed as the ...
A Kundu +6 more
core +1 more source
Multi-utility Learning: Structured-output Learning with Multiple Annotation-specific Loss Functions [PDF]
, 2014 Structured-output learning is a challenging problem; particularly so because of the difficulty in obtaining large datasets of fully labelled instances for training.
A. Delong +10 more
core +3 more sources
Proceedings of the 10th International Conference on Computer Vision Theory and Applications, 2015 Superpixel segmentation is widely used in the preprocessing step of many applications. Most of existing methods are based on a photometric criterion combined to the position of the pixels. In the same way as the Simple Linear Iterative Clustering (SLIC) method, based on k-means segmentation, a new algorithm is introduced.
Bauda, Marie-Anne +3 more
openaire +2 more sources
Brain and Behavior, Volume 16, Issue 5, May 2026.Tablet‐based handwriting tasks (spiral, meander, and wave) are transformed into unified images and analyzed using PD‐MGMA‐DSCNN, a lightweight multiscale gated attention network. Bayesian–genetic optimization improves performance, while SHAP attribution maps provide interpretable handwriting biomarkers for Parkinson's disease screening.
Khosro Rezaee, Ali Khalili Fakhrabadi
wiley +1 more source
An Improved Image Semantic Segmentation Method Based on Superpixels and Conditional Random Fields
Applied Sciences, 2018 This paper proposed an improved image semantic segmentation method based on superpixels and conditional random fields (CRFs). The proposed method can take full advantage of the superpixel edge information and the constraint relationship among different ...
Wei Zhao, Yi Fu, Xiaosong Wei, Hai Wang
doaj +1 more source
Region-based Skin Color Detection. [PDF]
, 2012 Skin color provides a powerful cue for complex computer vision applications. Although skin color detection has been an active research area for decades, the mainstream technology is based on the individual pixels. This paper presents a new region-based
Liu, D. +3 more
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