Results 91 to 100 of about 2,106 (179)

Trainable superpixel segmentation

, 2018
Trainable Superpixel Segmentation is a plug-in developed for the ImageJ platform that aims at providing its users with the ability to train models to segment images by classifying superpixels using region-based image features. This project provides an underlying library that can be used independently, a graphic interface for ease of use and an ...
openaire   +1 more source

A Graph-Based Superpixel Segmentation Approach Applied to Pansharpening. [PDF]

Sensors (Basel)
Hallabia H.
europepmc   +1 more source

Sagittal balance parameters measurement on cervical spine MR images based on superpixel segmentation. [PDF]

Front Bioeng Biotechnol
Zhong YF, Dai YX, Li SP, Zhu KJ, Lin YP, Ran Y, Chen L, Ruan Y, Yu PF, Li L, Li WX, Xu CL, Sun ZT, Weber KA, Kong DW, Yang F, Lin WP, Chen J, Chen BL, Jiang H, Zhou YJ, Sheng B, Wang YJ, Tian YZ, Sun YL.   +24 more
europepmc   +1 more source

Superpixel Random Selection Random Walk Multi-Branch Depthwise Convolutional Neural Network for Hyperspectral Image Classification. [PDF]

Sensors (Basel)
Zhang K, Jiang X, Cai Z.
europepmc   +1 more source

Free Space Estimation Based on Superpixel Clustering for Assisted Driving. [PDF]

Sensors (Basel)
Vitales O, Aguilar-Ponce R, Vigueras J.
europepmc   +1 more source

Detection of collagen band-associated regions in H&E-stained colonic biopsies of collagenous colitis patients using superpixel-based feature extraction and neural network classification. [PDF]

Diagn Pathol
Kiudelis V, Petrolis R, Ramonaitė R, Jančiauskas D, Poškienė L, Kupčinskas J, Šabanas P, Čerapaitė-Trušinskienė R, Meilutytė-Lukauskienė D, Kriščiukaitis A.   +9 more
europepmc   +1 more source

Explainable deep learning-based lung cancer diagnosis using clinically-guided local interpretable model-agnostic explanations. [PDF]

Sci Rep
Hassan SU, Abdulkadir SJ, Alhussian HS, Fayyaz AM, Al-Selwi SM, Khan U, Ismail AOA.   +6 more
europepmc   +1 more source

A Fast Superpixel Segmentation Algorithm for PolSAR Images Based on Edge Refinement and Revised Wishart Distance. [PDF]

Sensors (Basel), 2016
Zhang Y, Zou H, Luo T, Qin X, Zhou S, Ji K.   +5 more
europepmc   +1 more source

Deep Learning-Based Automatic Segmentation of Ischemic Stroke Lesions in CT Perfusion Imaging. [PDF]

Biomimetics (Basel)
Zare Lahijan L, Meshgini S, Afrouzian R.
europepmc   +1 more source