VRSDNet: vehicle re-identification with a shortly and densely connected convolutional neural network
Sign Up to like & getrecommendations! Published in 2018 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-018-6270-4
Abstract: Vehicle re-identification aiming to match vehicle images captured by different cameras plays an important role in video surveillance for public security. In this paper, we solve Vehicle Re-identification with a Shortly and Densely connected convolutional… read more here.
Keywords: connected convolutional; vehicle; vrsdnet; vehicle identification ... See more keywords
Lightweight residual densely connected convolutional neural network
Sign Up to like & getrecommendations! Published in 2020 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-020-09223-8
Abstract: Extremely efficient convolutional neural network architectures are one of the most important requirements for limited-resource devices (such as embedded and mobile devices). The computing power and memory size are two important constraints of these devices.… read more here.
Keywords: lightweight residual; convolutional neural; residual densely; neural network ... See more keywords
A multi-purpose image forensic method using densely connected convolutional neural networks
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Real-Time Image Processing"
DOI: 10.1007/s11554-019-00866-x
Abstract: Multi-purpose forensics is attracting increasing attention worldwide. In this paper, we propose a multi-purpose method based on densely connected convolutional neural networks (CNNs) for simultaneous detection of 11 different types of image manipulations. An efficient… read more here.
Keywords: multi purpose; connected convolutional; image; method ... See more keywords
Lightweight densely connected residual network for human pose estimation
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Real-Time Image Processing"
DOI: 10.1007/s11554-020-01025-3
Abstract: Most existing methods pay much attention to how to improve the accuracy of human pose estimation results. They usually ignore what the size of their model is. However, besides accuracy, real-time and speed are also… read more here.
Keywords: human pose; network; pose estimation; connected residual ... See more keywords
Densely connected attention network for diagnosing COVID-19 based on chest CT
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DOI: 10.1016/j.compbiomed.2021.104857
Abstract: Background To fully enhance the feature extraction capabilities of deep learning models, so as to accurately diagnose coronavirus disease 2019 (COVID-19) based on chest CT images, a densely connected attention network (DenseANet) was constructed by… read more here.
Keywords: attention features; attention; connected attention; covid based ... See more keywords
Image super-resolution via a densely connected recursive network
Sign Up to like & getrecommendations! Published in 2018 at "Neurocomputing"
DOI: 10.1016/j.neucom.2018.07.076
Abstract: Abstract The single-image super-resolution techniques (SISR) have been significantly promoted by deep networks. However, the storage and computation complexities of deep models increase dramatically alongside with the reconstruction performance. This paper proposes a densely connected… read more here.
Keywords: super resolution; recursive network; connected recursive; image super ... See more keywords
Deep convolutional neural network based on densely connected squeeze-and-excitation blocks
Sign Up to like & getrecommendations! Published in 2019 at "AIP Advances"
DOI: 10.1063/1.5100577
Abstract: Convolutional neural networks have achieved great successes in many visual tasks, as well as a good performance in various applications. However, research has yet to solve the practical problem of how to improve the recognition… read more here.
Keywords: densely connected; squeeze excitation; network; convolutional neural ... See more keywords
Densely connected deep random forest for hyperspectral imagery classification
Sign Up to like & getrecommendations! Published in 2018 at "International Journal of Remote Sensing"
DOI: 10.1080/01431161.2018.1547932
Abstract: ABSTRACT In very recent years, deep learning based methods have been widely introduced for the classification of hyperspectral images (HSI). However, these deep models need lots of training samples to tune abundant parameters which induce… read more here.
Keywords: classification; connected deep; random forest; deep random ... See more keywords
A new attention-based 3D densely connected cross-stage-partial network for motor imagery classification in BCI
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Neural Engineering"
DOI: 10.1088/1741-2552/ac93b4
Abstract: Objective. The challenge for motor imagery (MI) in brain-computer interface (BCI) systems is finding a reliable classification model that has high classification accuracy and excellent robustness. Currently, one of the main problems leading to degraded… read more here.
Keywords: network; classification; densely connected; attention based ... See more keywords
Applications of Digital Microscopy and Densely Connected Convolutional Neural Networks for Automated Quantification of Babesia-Infected Erythrocytes.
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DOI: 10.1093/clinchem/hvab237
Abstract: BACKGROUND Clinical babesiosis is diagnosed, and parasite burden is determined, by microscopic inspection of a thick or thin Giemsa-stained peripheral blood smear. However, quantitative analysis by manual microscopy is subject to error. As such, methods… read more here.
Keywords: digital microscopy; microscopy; microscopy densely; applications digital ... See more keywords
Enhancement of Perivascular Spaces Using Densely Connected Deep Convolutional Neural Network
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2896911
Abstract: Perivascular spaces (PVS) in the human brain are related to various brain diseases. However, it is difficult to quantify them due to their thin and blurry appearance. In this paper, we introduce a deep-learning-based method,… read more here.
Keywords: neural network; densely connected; perivascular spaces; deep convolutional ... See more keywords