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Now showing items 41-46 of 46
IRv2-Net: A Deep Learning Framework for Enhanced Polyp Segmentation Performance Integrating InceptionResNetV2 and UNet Architecture with Test Time Augmentation Techniques
(
Multidisciplinary Digital Publishing Institute (MDPI)
, 2023 , Article)
Colorectal polyps in the colon or rectum are precancerous growths that can lead to a more severe disease called colorectal cancer. Accurate segmentation of polyps using medical imaging data is essential for effective ...
Robust and General Model to Forecast the Heat Transfer Coefficient for Flow Condensation in Multi Port Mini/Micro‐Channels
(
Multidisciplinary Digital Publishing Institute (MDPI)
, 2022 , Article)
A general correlation for predicting the two‐phase heat transfer coefficient (HTC) during condensation inside multi‐port mini/micro‐channels was presented. The model was obtained by correlating the two‐phase multiplier, ...
Explainable deep learning model for automatic mulberry leaf disease classification
(
Frontiers Media SA
, 2023 , Article)
Mulberry leaves feed Bombyx mori silkworms to generate silk thread. Diseases that affect mulberry leaves have reduced crop and silk yields in sericulture, which produces 90% of the world’s raw silk. Manual leaf disease ...
Development of a stacked machine learning model to compute the capability of ZnO-based sensors for hydrogen detection
(
Elsevier
, 2024 , Article)
Zinc oxide (ZnO) nanocomposite sensors decorated with various dopants are popular tools for detecting even low hydrogen (H2) concentrations. The nanocomposite's chemistry, temperature, and H2 concentration impact the success ...
Digitally-tuned resolver converter
(
Elsevier B.V.
, 2009 , Article)
Sinusoidal encoders provide electrical signals related to the sine and cosine of the mechanical shaft angle θ. An analog converter is described for the linearization of these signals and hence for linear computation of θ. ...
Robust estimation of highly-varying nonlinear instantaneous frequency of monocomponent signals using a lower-order complex-time distribution
(
Elsevier B.V.
, 2013 , Article)
This paper proposes an approach for robust estimation of highly-varying nonlinear instantaneous frequency (IF) in monocomponent nonstationary signals. The proposed method is based on a lower order complex-time distribution ...