Results 31 to 40 of about 549,628 (266)
BMC Medical Informatics and Decision Making, 2019 Background With the advancement of powerful image processing and machine learning techniques, Computer Aided Diagnosis has become ever more prevalent in all fields of medicine including ophthalmology.
Muhammad Naseer Bajwa +6 more
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Deep Learning Approaches Based on Transformer Architectures for Image Captioning Tasks
IEEE Access, 2022 This paper focuses on visual attention, a state-of-the-art approach for image captioning tasks within the computer vision research area. We study the impact that different hyperparemeter configurations on an encoder-decoder visual attention architecture ...
Roberto Castro +3 more
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Deep Learning in Proteomics [PDF]
PROTEOMICS, 2020 Abstract Proteomics, the study of all the proteins in biological systems, is becoming a data‐rich science. Protein sequences and structures are comprehensively catalogued in online databases. With recent advancements in tandem mass spectrometry (MS) technology, protein expression and post‐translational modifications (PTMs) can be ...
Bo Wen +6 more
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BiomimeticsIn recent years, unmanned aerial vehicle (UAV) technology has advanced significantly, enabling its widespread use in critical applications such as surveillance, search and rescue, and environmental monitoring.
Mingen Wang +6 more
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A Deep Learning Enabled Multi-Class Plant Disease Detection Model Based on Computer Vision
AI, 2021 In this paper, a deep learning enabled object detection model for multi-class plant disease has been proposed based on a state-of-the-art computer vision algorithm. While most existing models are limited to disease detection on a large scale, the current
Arunabha M. Roy, Jayabrata Bhaduri
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Trans. Mach. Learn. Res., 2023 Transfer learning has recently become the dominant paradigm of machine learning. Pre-trained models fine-tuned for downstream tasks achieve better performance with fewer labelled examples. Nonetheless, it remains unclear how to develop models that specialise towards multiple tasks without incurring negative interference and that generalise ...
Jonas Pfeiffer +3 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Pediatric radiation therapy presents unique challenges compared to adult treatments, including those of immobilization, potential need for sedation, and the critical importance of accurate, reproducible positioning. Additionally, heightened attention to imaging doses is necessary to minimize long‐term toxicity in survivors.
Parham Alaei +17 more
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UCL: Unsupervised Curriculum Learning for water body classification from remote sensing imagery
International Journal of Applied Earth Observations and Geoinformation, 2021 This paper presents a Convolutional Neural Networks (CNN) based Unsupervised Curriculum Learning approach for the recognition of water bodies to overcome the stated challenges for remote sensing based RGB imagery. The unsupervised nature of the presented
Nosheen Abid +6 more
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Optica, 2017 We demonstrate that a deep neural network can significantly improve optical microscopy, enhancing its spatial resolution over a large field-of-view and depth-of-field. After its training, the only input to this network is an image acquired using a regular optical microscope, without any changes to its design.
Yair Rivenson +5 more
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Early Impact of Childhood Opportunity on Neurocognitive Outcomes in Sickle Cell Disease
Pediatric Blood &Cancer, EarlyView.ABSTRACT Introduction Neurocognitive impairment is a well‐recognized complication of sickle cell disease (SCD) that begins early in childhood and persists across development. While cerebrovascular injury contributes substantially to risk, neurocognitive deficits are also observed in children without overt or silent cerebral infarctions, suggesting ...
Julia E. LaMotte +5 more
wiley +1 more source