Machine learning in image‐based outcome prediction after radiotherapy: A review
Sign Up to like & getrecommendations! Published in 2024 at "Journal of Applied Clinical Medical Physics"
DOI: 10.1002/acm2.14559
Abstract: Abstract The integration of machine learning (ML) with radiotherapy has emerged as a pivotal innovation in outcome prediction, bringing novel insights amid unique challenges. This review comprehensively examines the current scope of ML applications in… read more here.
Keywords: outcome prediction; learning image; radiotherapy; machine learning ... See more keywords
Generalizable, sequence‐invariant deep learning image reconstruction for subspace‐constrained quantitative MRI
Sign Up to like & getrecommendations! Published in 2025 at "Magnetic Resonance in Medicine"
DOI: 10.1002/mrm.30433
Abstract: To develop a deep subspace learning network that can function across different pulse sequences. read more here.
Keywords: deep learning; generalizable sequence; invariant deep; learning image ... See more keywords
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
Learning Image Fractals Using Chaotic Differentiable Point Splatting
Sign Up to like & getrecommendations! Published in 2025 at "Computer Graphics Forum"
DOI: 10.1111/cgf.70084
Abstract: Fractal geometry, defined by self‐similar patterns across scales, is crucial for understanding natural structures. This work addresses the fractal inverse problem, which involves extracting fractal codes from images to explain these patterns and synthesize them… read more here.
Keywords: image fractals; point splatting; differentiable point; learning image ... See more keywords