Results 41 to 50 of about 6,849,681 (296)
Government informatization model design based on emotional polarity analysis of network media in the context of deep learning [PDF]
PeerJ Computer ScienceIn response to the extensive and complex public comment data within the government system, this article presents an emotion analysis model for government information based on a dual attention multi-layer convolutional neural network (DA-MLCNN).
Jingyang Tang +3 more
doaj +2 more sources
Accurate Pixel-Wise Skin Segmentation Using Shallow Fully Convolutional Neural Network
IEEE Access, 2020 Skin segmentation plays an important role in human activity recognition, video surveillance, hand gesture identification, face detection, human tracking and robotic surgery.
Komal Minhas +7 more
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Saliency Detection With Fully Convolutional Neural Network
CoRR, 2019 Saliency detection is an important task in image processing as it can solve many problems and it usually is the first step in for other processes. Convolutional neural networks have been proved to be very effective on several image processing tasks such as classification, segmentation, semantic colorization and object manipulation.
Hooman Misaghi +3 more
openaire +3 more sources
A Fully Connected Quantum Convolutional Neural Network for Classifying Ischemic Cardiopathy
IEEE Access, 2022 The prevalence of heart diseases is rising quickly throughout the world, which has an impact on both the world economy and public health. According to the recent statistical survey reports, the increasing mortality rate is due to high blood pressure ...
Ubaid Ullah +3 more
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sagieppel/Fully-convolutional-neural-network-FCN-for-semantic-segmentation-with-pytorch: 1.0
, 2021 <p>1</p ...
sagieppel
core +1 more source
SC-PNN: Saliency Cascade Convolutional Neural Network for Pansharpening
, 2021 In many remote sensing tasks, different types of regions or targets differ in requirements for spectral and spatial quality. The discrepancy reveals that a uniform pansharpening strategy applying to the entire image may not fulfill the varying demands of
Zhang, Jue +3 more
core +1 more source
Fully convolutional neural networks improve abdominal organ segmentation [PDF]
Medical Imaging 2018: Image Processing, 2018 Abdominal image segmentation is a challenging, yet important clinical problem. Variations in body size, position, and relative organ positions greatly complicate the segmentation process. Historically, multi-atlas methods have achieved leading results across imaging modalities and anatomical targets.
Meg F. Bobo +10 more
openaire +3 more sources
Complexity, 2021 This paper uses an improved deep learning algorithm to judge the rationality of the design of landscape image feature recognition. The preprocessing of the image is proposed to enhance the data.
Bin Hu
doaj +1 more source
A Lightweight Fully Convolutional Neural Network for SAR Automatic Target Recognition
Remote Sensing, 2021 Automatic target recognition (ATR) in synthetic aperture radar (SAR) images has been widely used in civilian and military fields. Traditional model-based methods and template matching methods do not work well under extended operating conditions (EOCs ...
Jimin Yu +3 more
doaj +1 more source