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Now showing items 11-20 of 37
Video surveillance using deep transfer learning and deep domain adaptation: Towards better generalization
(
Elsevier
, 2023 , Other)
Recently, developing automated video surveillance systems (VSSs) has become crucial to ensure the security and safety of the population, especially during events involving large crowds, such as sporting events. While ...
WSNet - Convolutional Neural Networkbased Word Spotting for Arabic and English Handwritten Documents
(
UIKTEN - Association for Information Communication Technology Education and Science
, 2022 , Article)
This paper proposes a new convolutional neural network architecture to tackle the problem of word spotting in handwritten documents. A Deep learning approach using a novel Convolutional Neural Network is developed for the ...
A comparative analysis to forecast carbon dioxide emissions
(
Elsevier Ltd
, 2022 , Article)
Despite the growing knowledge and commitment to climate change, carbon dioxide (CO2) emissions continue to rise dramatically throughout the planet. In recent years, the consequences of climate change have become more ...
Field data forecasting using lstm and bi-lstm approaches
(
MDPI
, 2021 , Article)
Water, an essential resource for crop production, is becoming increasingly scarce, while cropland continues to expand due to the world's population growth. Proper irrigation scheduling has been shown to help farmers improve ...
COV-ECGNET: COVID-19 detection using ECG trace images with deep convolutional neural network
(
Springer Science and Business Media Deutschland GmbH
, 2022 , Article)
The reliable and rapid identification of the COVID-19 has become crucial to prevent the rapid spread of the disease, ease lockdown restrictions and reduce pressure on public health infrastructures. Recently, several methods ...
MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network
(
Springer Science and Business Media Deutschland GmbH
, 2022 , Article)
Electroencephalogram (EEG) signals suffer substantially from motion artifacts when recorded in ambulatory settings utilizing wearable sensors. Because the diagnosis of many neurological diseases is heavily reliant on clean ...
Thermal Change Index-Based Diabetic Foot Thermogram Image Classification Using Machine Learning Techniques
(
MDPI
, 2022 , Article)
Diabetes mellitus (DM) can lead to plantar ulcers, amputation and death. Plantar foot thermogram images acquired using an infrared camera have been shown to detect changes in temperature distribution associated with a ...
A New Deep Learning Method for Accurate Cardiac Heart Failure Prediction from RR Interval Measurements
(
IEEE
, 2022 , Conference Paper)
cardiovascular diseases are the major cause of death worldwide. Early detection of heart failure will assist patients and medical professionals in taking better precautions to reduce risks. The objective of this study is ...
Brain mr image enhancement for tumor segmentation using 3d u-net
(
MDPI
, 2021 , Article)
MRI images are visually inspected by domain experts for the analysis and quantification of the tumorous tissues. Due to the large volumetric data, manual reporting on the images is subjective, cumbersome, and error prone. ...
Reliable tuberculosis detection using chest X-ray with deep learning, segmentation and visualization
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
Tuberculosis (TB) is a chronic lung disease that occurs due to bacterial infection and is one of the top 10 leading causes of death. Accurate and early detection of TB is very important, otherwise, it could be life-threatening. ...