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Machine learning in the Internet of Things: Designed techniques for smart cities
(
Elsevier B.V.
, 2019 , Article)
Machine learning is one of the emerging technologies that has grabbed the attention of academicians and industrialists, and is expected to evolve in the near future. Machine learning techniques are anticipated to provide ...
Breast cancer image classification using pattern-based Hyper Conceptual Sampling method
(
Elsevier Ltd
, 2018 , Article)
The increase in biomedical data has given rise to the need for developing data sampling techniques. With the emergence of big data and the rise of popularity of data science, sampling or reduction techniques have been ...
A machine learning framework for enhancing digital experiences in cultural heritage
(
Emerald Group Publishing Ltd.
, 2020 , Article)
Purpose: Digital tools have been used to document cultural heritage with high-quality imaging and metadata. However, some of the historical assets are totally or partially unlabeled and some are physically damaged, which ...
An integrated framework for the interaction and 3D visualization of cultural heritage
(
Springer
, 2023 , Article)
In this study, the aim is to design and develop a 3D acquisition, visualization, and interaction framework to preserve cultural heritage and provide new ways to enable museum visitors and cultural audiences to virtually ...
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 ...
Estimating blood pressure from the photoplethysmogram signal and demographic features using machine learning techniques
(
MDPI AG
, 2020 , Article)
Hypertension is a potentially unsafe health ailment, which can be indicated directly from the blood pressure (BP). Hypertension always leads to other health complications. Continuous monitoring of BP is very important; ...
A nomogram-based diabetic sensorimotor polyneuropathy severity prediction using Michigan neuropathy screening instrumentations
(
Elsevier
, 2021 , Article)
Background: Diabetic Sensorimotor polyneuropathy (DSPN) is one of the major indelible complications in diabetic patients. Michigan neuropathy screening instrumentation (MNSI) is one of the most common screening techniques ...
An investigation to study the effects of Tai Chi on human gait dynamics using classical machine learning
(
Elsevier
, 2022 , Article)
Tai Chi has been proven effective in preventing falls in older adults, improving the joint function of knee osteoarthritis patients, and improving the balance of stroke survivors. However, the effect of Tai Chi on human ...
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 ...
Performance analysis of conventional machine learning algorithms for diabetic sensorimotor polyneuropathy severity classification
(
MDPI
, 2021 , Article)
Background: Diabetic peripheral neuropathy (DSPN), a major form of diabetic neuropathy, is a complication that arises in long-term diabetic patients. Even though the application of machine learning (ML) in disease diagnosis ...