Deep convolutional neural network for preoperative prediction of microvascular invasion and clinical outcomes in patients with HCCs
Sign Up to like & getrecommendations! Published in 2021 at "European Radiology"
DOI: 10.1007/s00330-021-08198-w
Abstract: We aimed to develop and validate a deep convolutional neural network (DCNN) model for preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) and its clinical outcomes using contrast-enhanced computed tomography (CECT) in a… read more here.
Keywords: preoperative prediction; combined nomogram; validation; clinical outcomes ... See more keywords
A Comparison: Different DCNN Models for Intelligent Object Detection in Remote Sensing Images
Sign Up to like & getrecommendations! Published in 2018 at "Neural Processing Letters"
DOI: 10.1007/s11063-018-9878-5
Abstract: Abstract In recent years, deep learning especially deep convolutional neural networks (DCNN) has made great progress. Many researchers take advantage of different DCNN models to do object detection in remote sensing. Different DCNN models have different… read more here.
Keywords: object detection; detection remote; remote sensing; different dcnn ... See more keywords
Parkinson's disease detection and stage classification: quantitative gait evaluation through variational mode decomposition and DCNN architecture
Sign Up to like & getrecommendations! Published in 2024 at "Connection Science"
DOI: 10.1080/09540091.2024.2383894
Abstract: Parkinson's disease (PD) is a progressive, debilitating neurological movement disorder that affects the person's muscle control, movement, speech, cognition and dexterity. For diagnosing PD in a clinical setting, in addition to the neurological examinations, clinicians… read more here.
Keywords: gait; dcnn; parkinson disease; evaluation ... See more keywords
A deep ensemble dense convolutional neural network for rolling bearing fault diagnosis
Sign Up to like & getrecommendations! Published in 2021 at "Measurement Science and Technology"
DOI: 10.1088/1361-6501/ac05f5
Abstract: The accurate identification of rolling bearing fault based on unbalanced data has always been a challenge in the field of fault diagnosis. In some practical scenarios, since the machine is in the normal state most… read more here.
Keywords: fault; dense convolutional; convolutional neural; neural network ... See more keywords
SFUnet-DCNN: An Effective Approach for LPI Radar Waveform Recognition Under Low SNR Conditions
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Sensors Journal"
DOI: 10.1109/jsen.2025.3560442
Abstract: Low probability of intercept (LPI) radar waveform recognition is crucial in modern electronic defense, providing decision-makers with essential insights. However, LPI radar signals are highly susceptible to noise interference, especially in low signal-to-noise ratio (SNR)… read more here.
Keywords: recognition; snr; dcnn; approach ... See more keywords
Training Deep Convolutional Neural Networks for Land–Cover Classification of High-Resolution Imagery
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2017.2657778
Abstract: Deep convolutional neural networks (DCNNs) have recently emerged as a dominant paradigm for machine learning in a variety of domains. However, acquiring a suitably large data set for training DCNN is often a significant challenge.… read more here.
Keywords: imagery; image; remote sensing; cover classification ... See more keywords
Recognition and Classification of Mixed Defect Pattern Wafer Map Based on Multi-Path DCNN
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Semiconductor Manufacturing"
DOI: 10.1109/tsm.2024.3418520
Abstract: The semiconductor industry is the core industry of the information age. As a key link in the semiconductor industry, wafer fabrication plays a key role in its development. In the testing stage of the wafer,… read more here.
Keywords: classification; multi path; wafer map; mixed defect ... See more keywords
Rapid broad area search and detection of Chinese surface-to-air missile sites using deep convolutional neural networks
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Applied Remote Sensing"
DOI: 10.1117/1.jrs.11.042614
Abstract: Abstract. We evaluated how deep convolutional neural networks (DCNN) could assist in the labor-intensive process of human visual searches for objects of interest in high-resolution imagery over large areas of the Earth’s surface. Various DCNN… read more here.
Keywords: search; neural networks; deep convolutional; convolutional neural ... See more keywords
Automated Segmentation of Mass Regions in DBT Images Using a Dilated DCNN Approach
Sign Up to like & getrecommendations! Published in 2022 at "Computational Intelligence and Neuroscience"
DOI: 10.1155/2022/9082694
Abstract: To overcome the limitations of conventional breast screening methods based on digital mammography, a quasi-3D imaging technique, digital breast tomosynthesis (DBT) has been developed in the field of breast cancer screening in recent years. In… read more here.
Keywords: dcnn; dbt images; images using; mass regions ... See more keywords
Leukemia classification using the deep learning method of CNN.
Sign Up to like & getrecommendations! Published in 2022 at "Journal of X-ray science and technology"
DOI: 10.3233/xst-211055
Abstract: BACKGROUND Processing Low-Intensity Medical Images (LI-MI) is difficult as outcomes are varied when it comes to manual examination, which is also a time-consuming process. OBJECTIVE To improve the quality of low-intensity images and identify the… read more here.
Keywords: dcnn; classification; leukemia classification; deep learning ... See more keywords
Compact Spatial Pyramid Pooling Deep Convolutional Neural Network Based Hand Gestures Decoder
Sign Up to like & getrecommendations! Published in 2020 at "Applied Sciences"
DOI: 10.3390/app10217898
Abstract: Current deep learning convolutional neural network (DCNN) -based hand gesture detectors with acute precision demand incredibly high-performance computing power. Although DCNN-based detectors are capable of accurate classification, the sheer computing power needed for this form… read more here.
Keywords: neural network; spatial pyramid; convolutional neural; hand ... See more keywords