Results 141 to 150 of about 18,989 (190)

Cross-domain dynamic routing decoders for multi-domain generalization in ultrasound imaging. [PDF]

open access: yesQuant Imaging Med Surg
Wu Z   +7 more
europepmc   +1 more source

Enhancing Oral Health Diagnostics With Hyperspectral Imaging and Computer Vision: Clinical Dataset Study.

open access: yesJMIR Med Inform
Römer P   +9 more
europepmc   +1 more source

C-FCN: Corners-based fully convolutional network for visual object detection

open access: closedMultimedia Tools and Applications, 2020
Object detection has achieved significantly progresses in recent years. Proposal-based methods have become the mainstream object detectors, achieving excellent performance on accurate recognition and localization of objects. However, region proposal generation is still a bottleneck.
Lin Jiao, Rujing Wang, Chengjun Xie
openalex   +2 more sources

Ellipse-FCN: Oil Tanks Detection from Remote Sensing Images with Fully Convolution Network

open access: closedIGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, 2020
Oil is an essential asset for every country, and plays a key role in world trade system. The detection of oil tanks is a very important task for both military and commerce. Recently, researchers have shown an increasing interest in oil tanks detection in remote sensing imagery.
Ziteng Cui   +4 more
openalex   +2 more sources

Text or Non-text Image Classification using Fully Convolution Network (FCN)

open access: closed2020 International Conference on Contemporary Computing and Applications (IC3A), 2020
The semantic information in a natural scene plays a vital role in image understanding. One of the semantic information present in a natural image is the text. It can be utilized for analyzing several computer vision applications. The proposed work focuses on the new task of classifying the text images from a bulk of natural images.
Neeraj Gupta, Anand Singh Jalal
openalex   +2 more sources

L-FCN: A lightweight fully convolutional network for biomedical semantic segmentation

open access: closed2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2018
For the past few years, deep learning-based methods have been widely used in the field of biomedical imaging. In biomedical image processing, the typical application of deep learning is semantic segmentation. However, the classical deep learning methods require higher hardware consumption and computational costs.
Kaiyue Li, Guangtai Ding, Haitao Wang
openalex   +2 more sources

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