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TernausNetV2: Fully Convolutional Network for Instance Segmentation [PDF]

2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2018
The most common approaches to instance segmentation are complex and use two-stage networks with object proposals, conditional random-fields, template matching or recurrent neural networks. In this work we present TernausNetV2 - a simple fully convolutional network that allows extracting objects from a high-resolution satellite imagery on an instance ...
Vladimir I. Iglovikov, Selim S. Seferbekov, Alexander V. Buslaev, Alexey Shvets   +3 more
openaire   +3 more sources

Fully convolutional geometric features

, 2019
Extracting geometric features from 3D scans or point clouds is the first step in applications such as registration, reconstruction, and tracking. State-of-the-art methods require computing low-level features as input or extracting patch-based features ...
Park, Jaesik, Choy, Christopher, Koltun, Vladlen   +2 more
core   +1 more source

Multimodal Data‐Driven Microstructure Characterization

Advanced Engineering Materials, EarlyView.
A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang, Santiago Benito, Özge Özgün, Sebastian Weber, Markus Stricker   +4 more
wiley   +1 more source

Fully-Cascaded Spatial-Aware Convolutional Network for Motion Deblurring

Information
Motion deblurring is an ill-posed, challenging problem in image restoration due to non-uniform motion blurs. Although recent deep convolutional neural networks have made significant progress, many existing methods adopt multi-scale or multi-patch ...
Yinghan Hong, Bishenghui Tao, Qian Wang, Guizhen Mai, Cai Guo   +4 more
doaj   +1 more source

Region-Based Removal of Thermal Reflection Using Pruned Fully Convolutional Network

IEEE Access, 2020
In general, an image obtained from a thermal camera often has a mirror reflection or shadow reflected off the ground around an object, which is referred to as thermal reflection. Sometimes the thermal reflections are connected to their objects in images,
Ganbayar Batchuluun, Na Rae Baek, Dat Tien Nguyen, Tuyen Danh Pham, Kang Ryoung Park   +4 more
doaj   +1 more source

Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying

Advanced Engineering Materials, EarlyView.
An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara, Vincent Rat, Quentin Dubreuil, Patrice Valorge, Simon Goutier, Alain Denoirjean, Olivier Messe, Céline Ruelle, Jean‐Philippe Poli   +8 more
wiley   +1 more source

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

Advanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran, Vincent Nebel, Dominik Perius, Kshitij Kumar, Yannis Heim, Laura Bies, Tobias Kraus   +6 more
wiley   +1 more source

Hybrid Attention-Based Encoder–Decoder Fully Convolutional Network for PolSAR Image Classification

Remote Sensing, 2023
Recently, methods based on convolutional neural networks (CNNs) achieve superior performance in polarimetric synthetic aperture radar (PolSAR) image classification.
Zheng Fang, Gong Zhang, Qijun Dai, Biao Xue, Peng Wang   +4 more
doaj   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

PolSAR-SFCGN: An End-to-End PolSAR Superpixel Fully Convolutional Generation Network

Remote Sensing
Polarimetric Synthetic Aperture Radar (PolSAR) image classification is one of the most important applications in remote sensing. The impressive superpixel generation approaches can improve the efficiency of the subsequent classification task and restrain
Mengxuan Zhang, Jingyuan Shi, Long Liu, Wenbo Zhang, Jie Feng, Jin Zhu, Boce Chu   +6 more
doaj   +1 more source