Results 101 to 110 of about 6,343,053 (206)

An Object-Based Image Analysis Method for Enhancing Classification of Land Covers Using Fully Convolutional Networks and Multi-View Images of Small Unmanned Aerial System

Remote Sensing, 2018
Fully Convolutional Networks (FCN) has shown better performance than other classifiers like Random Forest (RF), Support Vector Machine (SVM) and patch-based Deep Convolutional Neural Network (DCNN), for object-based classification using orthoimage only ...
Tao Liu, Amr Abd-Elrahman
doaj   +1 more source

Weakly supervised fully convolutional networks using OBIA classification output

, 2019
In this paper, we present a methodology for preparing reference data to be used in training a fully convolutional neural network. It is a laborious and time-consuming task to prepare adequate training data for a Fully convolutional network (FCN) since ...
Vanhuysse, Sabine, Stefanos Georganos, Moritz Lennert, Tais Grippa, Grippa, Taïs, Eleonore Wolff, Sabine Vanhuysse, Lennert, Moritz, Wolff, Eléonore, Mboga, Nicholus O., Georganos, Stefanos, Nicholus Mboga   +11 more
core   +1 more source

Promises and limitations of deep learning for predicting knee osteoarthritis progression from medical imaging: A systematic review

Knee Surgery, Sports Traumatology, Arthroscopy, Volume 34, Issue 11, Page 4219-4234, November 2026.
Abstract Purpose To systematically evaluate the performance, methodological quality, and translational barriers of deep learning (DL) models for predicting knee osteoarthritis (KOA) progression from medical imaging. Methods Following PRISMA guidelines, we searched PubMed, Scopus, and Web of Science (inception to June 2026) for peer‐reviewed studies ...
Amna Gillani, Rüdiger von Eisenhart‐Rothe, Klaus Woertler, Michael T. Hirschmann, Daniel Rueckert, Florian Hinterwimmer   +5 more
wiley   +1 more source

R-FCN++: Towards Accurate Region-Based Fully Convolutional Networks for Object Detection

, 2018
Region based detectors like Faster R-CNN and R-FCN have achieved leading performance on object detection benchmarks. However, in Faster R-CNN, RoI pooling is used to extract feature of each region, which might harm the classification as the RoI pooling ...
Li, Zeming, Chen, Yilun, Deng, Yangdong, Yu, Gang, Yilun Chen, Gang Yu, Yangdong Deng, Zeming Li   +7 more
core   +1 more source

Data‐driven thresholds for standardized classification of severe Alzheimer's disease neuropathology using digital neuropathology

Brain Pathology, Volume 36, Issue 6, November 2026.
We generated digital pathologic algorithms (AI‐based modules that can be freely shared) to: optimize the sampling (ROI) for diagnosis of ADNC‐related tau pathology; compare/transition between Aperio and HALO platforms; and rationalize severe Braak NFT staging, so that all Braak‐VI cases had dementia, and all Braak‐V cases had MCI or dementia.
Ryan K. Shahidehpour, Allison M. Neltner, Mitchell A. Klusty, Cole Corbett, Angelique D. Gonzalez, David A. Gutman, David W. Fardo, Adam D. Bachstetter, Cody Bumgardner, Margaret E. Flanagan, Peter T. Nelson   +10 more
wiley   +1 more source

A Semantic Segmentation Algorithm Using FCN with Combination of BSLIC

Applied Sciences, 2018
An image semantic segmentation algorithm using fully convolutional network (FCN) integrated with the recently proposed simple linear iterative clustering (SLIC) that is based on boundary term (BSLIC) is developed.
Wei Zhao, Haodi Zhang, Yujin Yan, Yi Fu, Hai Wang   +4 more
doaj   +1 more source

A new fully convolutional neural network for semantic segmentation of polarimetric SAR imagery in complex land cover ecosystem

, 2019
Despite the application of state-of-the-art fully Convolutional Neural Networks (CNNs) for semantic segmentation of very high-resolution optical imagery, their capacity has not yet been thoroughly examined for the classification of Synthetic Aperture ...
Molinier, Matthieu, Gill, Eric, Mohammadimanesh, Fariba, Salehi, Bahram, Mahdianpari, Masoud   +4 more
core   +1 more source

Computer Vision Pipeline for Image Analysis for Freeze‐Fracture Electron Microscopy: Rosette Cellulose Synthase Complexes Case

Advanced Intelligent Discovery, Volume 2, Issue 5, October 2026.
This paper presents a computer vision (deep learning) pipeline integrating YOLOv8 and YOLOv9 for automated detection, segmentation, and analysis of rosette cellulose synthase complexes in freeze‐fracture electron microscopy images. The study explores curated dataset expansion for model improvement and highlights pipeline accuracy, speed ...
Siri Mudunuri, Leala Carbonneau, Eric M. Roberts, Alison W. Roberts, Candace H. Haigler, Alexey V. Gulyuk, Yaroslava G. Yingling   +6 more
wiley   +1 more source

Straintronics and Twistronics in 2D Materials: Structural Control and Predictive Design

Small, Volume 22, Issue 56, 8 October 2026.
Strain and twist engineering in 2D materials is established as a programmable design parameter responsible for reconstructing lattices, tuning interlayer coupling, and developing new quantum functionalities. Through the integration of advanced fabrication techniques, multiscale characterization, computational modeling, and machine learning, this review
Manoj Tripathi, Sathvik Ajay Iyengar, Hannah J. Wood, Alexander Sredenschek, Md Hasan‐Ur Rahman, Surbhi Slathia, Xinting Shuai, Chandra Sekhar Tiwary, Etienne Z. Gnimpieba, Aditya D. Mohite, Mauricio Terrones, Pulickel M. Ajayan, Venkataramana Gadhamshetty, Vincent Meunier, Alan B. Dalton   +14 more
wiley   +1 more source

Asymmetric Encoder-Decoder Structured FCN Based LiDAR to Color Image Generation

Sensors, 2019
In this paper, we propose a method of generating a color image from light detection and ranging (LiDAR) 3D reflection intensity. The proposed method is composed of two steps: projection of LiDAR 3D reflection intensity into 2D intensity, and color image ...
Hyun-Koo Kim, Kook-Yeol Yoo, Ju H. Park, Ho-Youl Jung   +3 more
doaj   +1 more source