Sinogram-based deep learning image reconstruction technique in abdominal CT: image quality considerations
Sign Up to like & getrecommendations! Published in 2021 at "European Radiology"
DOI: 10.1007/s00330-021-07952-4
Abstract: To investigate the image quality and perception of a sinogram-based deep learning image reconstruction (DLIR) algorithm for single-energy abdominal CT compared to standard-of-care strength of ASIR-V. In this retrospective study, 50 patients (62% F; 56.74… read more here.
Keywords: image; image quality; learning image; deep learning ... See more keywords
Few-shot contrastive learning for image classification and its application to insulator identification
Sign Up to like & getrecommendations! Published in 2021 at "Applied Intelligence"
DOI: 10.1007/s10489-021-02769-6
Abstract: This paper presents a novel discriminative Few-shot learning architecture based on batch compact loss. Currently, Convolutional Neural Network (CNN) has achieved reasonably good performance in image recognition. Most existing CNN methods facilitate classifiers to learn… read more here.
Keywords: image; learning image; shot; image classification ... See more keywords
Deep learning for image-based weed detection in turfgrass
Sign Up to like & getrecommendations! Published in 2019 at "European Journal of Agronomy"
DOI: 10.1016/j.eja.2019.01.004
Abstract: Abstract Precision spraying of herbicides can significantly reduce herbicide use. The detection system is the critical component within smart sprayers that is used to detect target weeds and make spraying decisions. In this work, we… read more here.
Keywords: image based; based weed; bermudagrass; learning image ... See more keywords
Online Continual Learning in Image Classification: An Empirical Survey
Sign Up to like & getrecommendations! Published in 2022 at "Neurocomputing"
DOI: 10.1016/j.neucom.2021.10.021
Abstract: Online continual learning for image classification studies the problem of learning to classify images from an online stream of data and tasks, where tasks may include new classes (class incremental) or data nonstationarity (domain incremental).… read more here.
Keywords: learning; image classification; continual learning; online continual ... See more keywords
Deep Learning Image Analysis of Nanoplasmonic Sensors: Toward Medical Breath Monitoring.
Sign Up to like & getrecommendations! Published in 2022 at "ACS applied materials & interfaces"
DOI: 10.1021/acsami.2c11153
Abstract: Sensing biomarkers in exhaled breath offers a potentially portable, cost-effective, and noninvasive strategy for disease diagnosis screening and monitoring, while high sensitivity, wide sensing range, and target specificity are critical challenges. We demonstrate a deep… read more here.
Keywords: breath; image analysis; monitoring; deep learning ... See more keywords
Deep learning image segmentation and extraction of blueberry fruit traits associated with harvestability and yield
Sign Up to like & getrecommendations! Published in 2020 at "Horticulture Research"
DOI: 10.1038/s41438-020-0323-3
Abstract: Fruit traits such as cluster compactness, fruit maturity, and berry number per clusters are important to blueberry breeders and producers for making informed decisions about genotype selection related to yield traits and harvestability as well… read more here.
Keywords: fruit; learning image; blueberry; image segmentation ... See more keywords
Deep Learning and Image Processing Techniques for Recognizing Liquid-Crystal Display Array Residue and the Automatic Planning of Laser-Cutting Segments
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2022.3188550
Abstract: Defect detection in thin-film transistor liquid-crystal displays (TFT-LCDs) is crucial for ensuring the quality of the display. However, because of the diversity of TFT-LCD panel defects, accurate localization and detection become difficult. To overcome these… read more here.
Keywords: display; liquid crystal; laser cutting; deep learning ... See more keywords
Deep Learning in Image Analysis for COVID-19 Diagnosis: a Survey
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Latin America Transactions"
DOI: 10.1109/tla.2021.9451237
Abstract: COVID-19 achieved the highest concentration of confirmed cases in the Americas with a significant impact in Latin America and the Caribbean region, where access to water and sanitation is restricted. In this scenario, we surveyed… read more here.
Keywords: diagnosis; analysis covid; image analysis; learning image ... See more keywords
Deep Learning Image Reconstruction for CT: Technical Principles and Clinical Prospects.
Sign Up to like & getrecommendations! Published in 2023 at "Radiology"
DOI: 10.1148/radiol.221257
Abstract: Filtered back projection (FBP) has been the standard CT image reconstruction method for 4 decades. A simple, fast, and reliable technique, FBP has delivered high-quality images in several clinical applications. However, with faster and more… read more here.
Keywords: quality; learning image; reconstruction; deep learning ... See more keywords
Deep learning image transmission through a multimode fiber based on a small training dataset.
Sign Up to like & getrecommendations! Published in 2022 at "Optics express"
DOI: 10.1364/oe.450999
Abstract: An improved deep neural network incorporating attention mechanism and DSSIM loss function (AM_U_Net) is used to recover input images with speckles transmitted through a multimode fiber (MMF). The network is trained on a relatively small… read more here.
Keywords: multimode fiber; fiber; image transmission; deep learning ... See more keywords