6 hasil untuk "Nandini Modi"
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Artikel Jurnal
Use of information modelling techniques to understand research trends in eye gaze estimation methods: An automated review
Eye gaze tracking has been used to study the influence of visual stimuli on consumer behavior and attentional processes. Eye gaze tracking techniques have made substantial contributions in advertisement design, human computer interaction, virtual reality and disease diagnosis. Eye gaze estimation…
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Artikel Jurnal
Explainable YOLO models for early skin cancer detection using hair artifact removal and VGG16 guided annotation
Abstract Skin cancer is among the most common and potentially lethal diseases globally, emphasizing the need for early and accurate detection. Deep learning, particularly object detection models, has shown significant promise in dermatological image analysis. This study introduces a YOLO, a deep…
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Artikel Jurnal
Deep transfer learning and contour-based morphological analysis for detection of eye-hypertensive diseases from fundus images
Abstract Hypertensive eye disease produces subtle retinal changes that are often challenging for automated systems to recognize reliably. This paper proposes a hybrid diagnostic framework that combines contour-based morphological descriptors with deep transfer learning to classify hypertensive…
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Artikel Jurnal
Physiological signal-based mental stress detection using hybrid deep learning models
Abstract Mental stress is on the rise in all professions due to the fast pace of modern life and the transition in employment from physical to cognitive work. Mental stress is increasingly a major source of work-related illness. A sedentary lifestyle and work environment require individuals to work…
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Artikel Jurnal
A comparative evaluation of deep learning models for the classification of encoded splice-junction sequences
IntroductionComputational classifiers can be benchmarked against public encoded splice-junction datasets, but the performance estimate will depend on the input representation, preprocessing pipeline, model set-up and evaluation design.MethodsThis study investigates the performance of 15 different…
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Artikel Jurnal
Automating cancer diagnosis using advanced deep learning techniques for multi-cancer image classification
Abstract Cancer detection poses a significant challenge for researchers and clinical experts due to its status as the leading cause of global mortality. Early detection is crucial, but traditional cancer detection methods often rely on invasive procedures and time-consuming analyses, creating a…