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Smart neuropathy detection using machine intelligence: Filling the void between clinical practice and early diagnosis
(
Institute of Electrical and Electronics Engineers Inc.
, 2019 , Conference Paper)
An important aspect of Smart healthcare involves the development of innovative non-intrusive procedures for early detection and diagnosis of specific illnesses. Essentially, diseases for which very complicated and invasive ...
Classification ensemble to improve medical named entity recognition
(
Institute of Electrical and Electronics Engineers Inc.
, 2014 , Conference Paper)
An accurate Named Entity Recognition (NER) is important for knowledge discovery in text mining. This paper proposes an ensemble machine learning approach to recognise Named Entities (NEs) from unstructured and informal ...
On the detection of Kernel-level rootkits using hardware performance counters
(
Association for Computing Machinery, Inc
, 2017 , Conference Paper)
Recent work has investigated the use of hardware perfor- mance counters (HPCs) for the detection of malware run- ning on a system. These works gather traces of HPCs for a variety of applications (both malicious and ...
Machine Learning-based Regression and Classification Models for Oil Assessment of Power Transformers
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
Expensive and widely used power and distribution transformers need to be monitored to ensure the reliability of the power grid. Evaluating the transformer oil different parameters is vital to determine the transformer ...
Progressive image stitching algorithm for vision based automated inspection
(
IEEE Computer Society
, 2016 , Conference Paper)
The increasing number of skyscrapers along with the large number of tall bridges throughout the world also increases the demand of a robust, automated and remotely controlled health monitoring system for civil architectures. ...
Analysis of Unsupervised Consumption Anomaly Detection in Sports Facilities using Artificial Intelligence-Based Data Analytics: A Case Study
(
Association for Computing Machinery (ACM)
, 2023 , Conference Paper)
Sports facilities have exceptionally high energy demand due to the extensive operational requirements and high-occupancy seasonal rates. Towards promoting efficient energy usage and minimal losses, consumption anomaly ...
Towards a multimodal classification of cultural heritage
(
Hamad bin Khalifa University Press (HBKU Press)
, 2018 , Conference Paper)
The humanity has always learned from the previous experiences and thus for many reasons. The national heritage proves to be a great way to discover and access a nation's history. As a result, these priceless cultural items ...
Machine Learning Methods for Dysgraphia Screening with Online Handwriting Features
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Conference Paper)
Dysgraphia, a major learning disorder that primarily interferes with writing skills can hinder the academic track of children unless recognized in the early stage. The diversity in the symptoms, as well as the emergence ...
Dairy Cow Rumination Detection: A Deep Learning Approach
(
Springer Science and Business Media Deutschland GmbH
, 2020 , Conference Paper)
Cattle activity is an essential index for monitoring health and welfare of the ruminants. Thus, changes in the livestock behavior are a critical indicator for early detection and prevention of several diseases. Rumination ...
Enhancing Safety in Geological Carbon Sequestration: Supervised Machine Learning for Early Detection and Mitigation of CO2 Leakage in Injection Wells
(
International Petroleum Technology Conference (IPTC)
, 2024 , Conference Paper)
The efficient and safe operation of CO2 injection wells during geological sequestration is crucial for successful carbon capture and storage (CCS) projects. This study explores the application of machine learning in creating ...