HIDM: Hybrid intrusion detection model for industry 4.0 Networks using an optimized CNN-LSTM with transfer learning

UK Lilhore, P Manoharan, S Simaiya, R Alroobaea… - Sensors, 2023 - mdpi.com
Industrial automation systems are undergoing a revolutionary change with the use of
Internet-connected operating equipment and the adoption of cutting-edge advanced …

Enhanced convolutional neural network model for cassava leaf disease identification and classification

UK Lilhore, AL Imoize, CC Lee, S Simaiya, SK Pani… - Mathematics, 2022 - mdpi.com
Cassava is a crucial food and nutrition security crop cultivated by small-scale farmers and it
can survive in a brutal environment. It is a significant source of carbohydrates in African …

PoxNet22: A fine-tuned model for the classification of monkeypox disease using transfer learning

F Yasmin, MM Hassan, M Hasan, S Zaman… - Ieee …, 2023 - ieeexplore.ieee.org
Officials in the field of public health are concerned about a new monkeypox outbreak, even
though the world is now experiencing an epidemic of COVID-19. Similar to variola, cowpox …

Fundamental pillars for industry 4.0 development: implementation framework and challenges in manufacturing environment

M Singh, R Goyat, R Panwar - The TQM Journal, 2023 - emerald.com
Purpose At the present time, Industry 4.0 has proven its effectiveness and significance in
automation and data exchange within industries across different sectors worldwide. In the …

A smart waste classification model using hybrid CNN-LSTM with transfer learning for sustainable environment

UK Lilhore, S Simaiya, S Dalal… - Multimedia Tools and …, 2024 - Springer
Waste collection, classification, and planning have become crucial as industrialization and
smart city advancement activities have increased. A recycling process of waste relies on the …

A survey of methods for automated quality control based on images

J Diers, C Pigorsch - International Journal of Computer Vision, 2023 - Springer
The role of quality control based on images is important in industrial production.
Nevertheless, this problem has not been addressed in computer vision for a long time. In …

Machine learning and deep learning approach to Parkinson's disease detection: present state-of-the-art and a bibliometric review

G Sabherwal, A Kaur - Multimedia Tools and Applications, 2024 - Springer
Parkinson's disease (PD) is fatal, severe and irreversible neurological disorder. With the
aging of the world population, the prevalence of PD is on the rise, making it the second most …

A hybrid deep learning model using CNN and K-Mean clustering for energy efficient modelling in mobile EdgeIoT

D Bisen, UK Lilhore, P Manoharan, F Dahan… - Electronics, 2023 - mdpi.com
In mobile edge computing (MEC), it is difficult to recognise an optimum solution that can
perform in limited energy by selecting the best communication path and components. This …

Feature-guided multimodal sentiment analysis towards Industry 4.0

B Yu, J Wei, B Yu, X Cai, K Wang, H Sun, L Bu… - Computers and …, 2022 - Elsevier
Abstarct Combining Artificial Intelligence (AI) to process rich media information has become
an important part of Industry 4.0. Sentiment recognition in AI aims to analyze user emotions …

Optimising air quality prediction in smart cities with hybrid particle swarm optimization‐long‐short term memory‐recurrent neural network model

S Dalal, UK Lilhore, N Faujdar, S Samiya… - IET Smart …, 2024 - Wiley Online Library
In smart cities, air pollution is a critical issue that affects individual health and harms the
environment. The air pollution prediction can supply important information to all relevant …