Results 111 to 120 of about 6,093,681 (207)

FCN+: Global Receptive Convolution Makes FCN Great Again

, 2023
Fully convolutional network (FCN) is a seminal work for semantic segmentation. However, due to its limited receptive field, FCN cannot effectively capture global context information which is vital for semantic segmentation.
Ye, Jin, Qiao, Yu, Deng, Zhongying, Ren, Xiaoyu, He, Junjun   +4 more
core  

Fully Convolutional Network Based Skeletonization for Handwritten Chinese Characters

, 2018
Structural analysis of handwritten characters relies heavily on robust skeletonization of strokes, which has not been solved well by previous thinning methods. This paper presents an effective fully convolutional network (FCN) to extract stroke skeletons
Liu, Cheng-Lin, Wang, Tie-Qiang
core   +1 more source

Improved fully convolutional network with conditional random field for building extraction [PDF]

, 2018
Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial TechnologiesBuilding extraction from remotely sensed imagery plays an important role in urban planning, disaster management, navigation ...
Shrestra, Sanjeevan
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Deformable Part-based Fully Convolutional Network for Object Detection

, 2017
Best Science PaperInternational audienceExisting region-based object detectors are limited to regions with fixed box geometry to represent objects, even if those are highly non-rectangular.
Cord, Matthieu, Thome, Nicolas, Henaff, Gilles, Mordan, Taylor   +3 more
core   +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

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

Object Instance Identification with Fully Convolutional Networks

, 2018
International audienceThis paper presents a novel approach for instance search and object detection, applied to museum visits. This approach relies on fully convo-lutional networks (FCN) to obtain region proposals and object representation.
Portaz, Maxime, Chevallet, Jean-Pierre, Jean-Pierre Chevallet, Philippe Mulhem, Matthias Kohl, Georges Quénot, Kohl, Matthias, Mulhem, Philippe, Quénot, Georges, Maxime Portaz   +9 more
core   +1 more source

Multispecies bird sound recognition using a fully convolutional neural network [PDF]

[EN] This study proposes a method based on fully convolutional neural networks (FCNs) to identify migratory birds from their songs, with the objective of recognizing which birds pass through certain areas and at what time.
García Rodríguez, Isaías, García Ordás, María Teresa, Rubio Martín, Sergio, Alaiz Moretón, Héctor, Benítez Andrades, José Alberto   +4 more
core   +1 more source

Deteksi Kerumunan Menggunakan Metode Fully-Convolutional Network pada Kamera Drone

, 2021
Dalam masa pandemi virus COVID-19 seperti saat perencanaan dan pelaksanaan tugas akhir ini membuat pemerintah menetapkan peraturan yang mengharuskan masyarakat untuk menerapkan beberapa protokol kesehatan salah satunya adalah dengan menghindari ...
Wishnu, Muhammad Fatih Fasiqulisan
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Comparative Analysis of Fully Convolutional Networks (FCN), SegNet, and U-Net for Semantic Segmentation of Synthetic Wafer Map Defect Patterns

Asian Journal of Advanced Research and Reports
Wafer defect maps serve as a primary diagnostic tool for process engineers, enabling the visualization of spatial defect distributions and the identification of potential equipment or process issues. As technology nodes shrink and device densities increase, the volume of inspection data has grown exponentially, rendering manual inspection impractical ...
openaire   +2 more sources