A review of deep learning models for time series prediction
Z Han, J Zhao, H Leung, KF Ma… - IEEE Sensors Journal, 2019 - ieeexplore.ieee.org
In order to approximate the underlying process of temporal data, time series prediction has
been a hot research topic for decades. Developing predictive models plays an important role …
been a hot research topic for decades. Developing predictive models plays an important role …
A novel hybrid deep learning model for metastatic cancer detection
Cancer has been found as a heterogeneous disease with various subtypes and aims to
destroy the body's normal cells abruptly. As a result, it is essential to detect and prognosis …
destroy the body's normal cells abruptly. As a result, it is essential to detect and prognosis …
[HTML][HTML] DeepBreastCancerNet: A novel deep learning model for breast cancer detection using ultrasound images
Breast cancer causes hundreds of women's deaths each year. The manual detection of
breast cancer is time-consuming, complicated, and prone to inaccuracy. For Breast Cancer …
breast cancer is time-consuming, complicated, and prone to inaccuracy. For Breast Cancer …
[HTML][HTML] Unveiling the future of breast cancer assessment: a critical review on generative adversarial networks in elastography ultrasound
Elastography Ultrasound provides elasticity information of the tissues, which is crucial for
understanding the density and texture, allowing for the diagnosis of different medical …
understanding the density and texture, allowing for the diagnosis of different medical …
Shallow 3D CNN for detecting acute brain hemorrhage from medical imaging sensors
Successive layers in convolutional neural networks (CNN) extract different features from
input images. Applications of CNNs to detect abnormalities in the 2D images or 3D volumes …
input images. Applications of CNNs to detect abnormalities in the 2D images or 3D volumes …
Automated mammogram breast cancer detection using the optimized combination of convolutional and recurrent neural network
RS Patil, N Biradar - Evolutionary intelligence, 2021 - Springer
The objective of this study is to frame mammogram breast detection model using the
optimized hybrid classifier. Image pre-processing, tumor segmentation, feature extraction …
optimized hybrid classifier. Image pre-processing, tumor segmentation, feature extraction …
[HTML][HTML] Detection and classification of histopathological breast images using a fusion of CNN frameworks
A Rafiq, A Chursin, W Awad Alrefaei… - Diagnostics, 2023 - mdpi.com
Breast cancer is responsible for the deaths of thousands of women each year. The diagnosis
of breast cancer (BC) frequently makes the use of several imaging techniques. On the other …
of breast cancer (BC) frequently makes the use of several imaging techniques. On the other …
An efficient compressive sensing routing scheme for internet of things based wireless sensor networks
Abstract Internet of Things (IoT) integrates diverse types of sensors, mobiles and other
technologies to physical world and IoT technology is used in a wide range of applications …
technologies to physical world and IoT technology is used in a wide range of applications …
Human visual system based unsharp masking for enhancement of mammographic images
Abstract Non-Linear Polynomial Filters (NPF) consists of a schema of linear and quadratic
filter components operating as a fusion of low-and high pass filters. NPF has shown …
filter components operating as a fusion of low-and high pass filters. NPF has shown …
An active microwave sensor for near field imaging
Near-field imaging using microwaves in medical applications is of great current interest for
its capability and accuracy in identifying features of interest, in comparison with other known …
its capability and accuracy in identifying features of interest, in comparison with other known …