Results 51 to 60 of about 10,393 (248)
Pupil Plane Multiplexing for Vectorial Fourier Ptychography
This study proposes a cost‐effective, modality‐adaptive multichannel microscopy framework using pupil‐plane multiplexing. A custom pupil aperture at the Fourier plane encodes channel‐specific transfer functions with spectral or polarization filters, and model‐based reconstruction with channel‐dependent priors decodes them.
Hyesuk Chae +5 more
wiley +1 more source
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
Learning to Segment Breast Biopsy Whole Slide Images
We trained and applied an encoder-decoder model to semantically segment breast biopsy images into biologically meaningful tissue labels. Since conventional encoder-decoder networks cannot be applied directly on large biopsy images and the different sized
Bartlett, Jamen +5 more
core +1 more source
A deep learning‐enabled toolkit for the 3D segmentation of ventricular cardiomyocytes
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
Interpretable Machine Learning: A Comprehensive Review of Foundations, Methods, and the Path Forward
This systematic review of 352 studies establishes a comprehensive taxonomy for Interpretable Machine Learning, transitioning from foundational intrinsic models to advanced deep learning explanations. It reveals a critical paradigm shift toward “mechanistic interpretability” and actionable recourse, emphasizing that future AI systems must be rigorously ...
Shimon Fridkin, Michael Bendersky
wiley +1 more source
Improved Spatial-Spectral Superpixel Hyperspectral Unmixing
In this paper, an unsupervised unmixing approach based on superpixel representation combined with regional partitioning is presented. A reduced-size image representation is obtained using superpixel segmentation where each superpixel is represented by ...
Mohammed Q. Alkhatib +1 more
doaj +1 more source
Superpixel Boundary-Based Edge Description Algorithm for SAR Image Segmentation
Although various methods can effectively segment synthetic aperture radar (SAR) images, we found that the method combining superpixel and image edge information can get better results. To solve the problem that common SAR image segmentation methods often
Ronghua Shang +4 more
doaj +1 more source
A Hybrid Model Based on Superpixel Entropy Discrimination for PolSAR Image Classification
Superpixel segmentation is widely used in polarimetric synthetic aperture radar (PolSAR) image classification. However, the classification method using simple majority voting cannot easily handle evidence conflicts in a single superpixel.
Jili Sun, Lingdong Geng, Yize Wang
doaj +1 more source
Superpixel-based Two-view Deterministic Fitting for Multiple-structure Data
This paper proposes a two-view deterministic geometric model fitting method, termed Superpixel-based Deterministic Fitting (SDF), for multiple-structure data.
AS Brahmachari +12 more
core +1 more source
Abstract As spherical shell mantle convection models become increasingly commonplace, understanding how plates are generated has raised the issue of how to recognize whether rigid plates are present in model output. Tectonocists have long recognized that intraplate regions are not rigid without exception.
P. Javaheri, J. P. Lowman
wiley +1 more source

