[HTML][HTML] Advancements in 3D digital model generation for digital twins in industrial environments: Knowledge gaps and future directions

M Kamali, B Atazadeh, A Rajabifard, Y Chen - Advanced Engineering …, 2024‏ - Elsevier
Digital twins are considered a transformative paradigm for industrial environments, providing
a dynamic, digital, and intelligent representation of industrial assets. The necessity of digital …

Unlocking the potential of keyword extraction: the need for access to high-quality datasets

ZH Amur, YK Hooi, GM Soomro, H Bhanbhro… - Applied Sciences, 2023‏ - mdpi.com
Keyword extraction is a critical task that enables various applications, including text
classification, sentiment analysis, and information retrieval. However, the lack of a suitable …

Revealing essential notions: an algorithmic approach to distilling core concepts from student and teacher responses in computer science education

ZH Amur, YK Hooi, GM Soomro… - Applied Computing and …, 2024‏ - emerald.com
Revealing essential notions: an algorithmic approach to distilling core concepts from student
and teacher responses in computer science education | Emerald Insight Books and journals …

Single Line Electrical Drawings (SLED): A Multiclass Dataset Benchmarked by Deep Neural Networks

H Bhanbhro, YK Hooi, MNB Zakaria… - 2023 IEEE 13th …, 2023‏ - ieeexplore.ieee.org
Single-line drawings have diverse applications across various industries, including electrical
substations, buildings, power distribution, maintenance, and more. Analyzing and …

Symbol Detection in a Multi-class Dataset Based on Single Line Diagrams using Deep Learning Models

H Bhanbhro, YK Hooi… - … Journal of Advanced …, 2023‏ - search.proquest.com
Abstract Single Line Diagrams (SLDs) are used in electrical power distribution systems.
These diagrams are crucial to engineers during the installation, maintenance, and …

MCBAN: A Small Object Detection Multi-Convolutional Block Attention Network.

H Bhanbhro, YK Hooi, MNB Zakaria… - Computers …, 2024‏ - search.ebscohost.com
Object detection has made a significant leap forward in recent years. However, the detection
of small objects continues to be a great difficulty for various reasons, such as they have a …

Support Vector Based Anomaly Detection in Federated Learning

M Frasson, D Malchiodi - … on Engineering Applications of Neural Networks, 2024‏ - Springer
Anomaly detection plays a crucial role in various domains. However, traditional centralized
approaches often encounter challenges related to data privacy. In this context, Federated …

Towards Digitisation of Technical Drawings in Architecture: Evaluation of CNN Classification on the Perdaw Dataset

A Filip, S Graßhof - … Conference on Engineering Applications of Neural …, 2024‏ - Springer
In a highly digitalised world, this paper aims at closing the gap towards automatic digitisation
from 2D architectural drawings. We present the new image dataset Plan, and Elevation …

Machine learning model for automated assessment of short subjective answers

ZH Amur, YK Hooi, H Bhanbro, MN Bhatti… - … Journal of Advanced …, 2023‏ - publikace.k.utb.cz
Natural Language Processing (NLP) has recently gained significant attention; where,
semantic similarity techniques are widely used in diverse applications, such as information …

Tumor Detection of Breast Tissue Using Random Forest with Principal Component Analysis

GM Soomro, S Krayem, ZH Amur… - 2023 IEEE 8th …, 2023‏ - ieeexplore.ieee.org
When it comes to cancer-related mortality, breast cancer is the most common and
predominant kind in women; lung cancer is the most common. It ranks second overall …