2 citations · 3 across the 10 of their papers we have counts for
4 papers · 1 filter
IoT-Enhanced CNN-Based Labelled Crack Detection for Additive Manufacturing Image Annotation in Industry 4.0
Mohsen Asghari Ilani, Yaser Mike Banad
This paper presents an IoT-enhanced deep learning framework for automated crack detection in Additive Manufacturing (AM) surfaces using convolutional neural networks (CNNs). By int…
TransMatch: A Transfer-Learning Framework for Defect Detection in Laser Powder Bed Fusion Additive Manufacturing
Mohsen Asghari Ilani, Yaser Mike Banad
Surface defects in Laser Powder Bed Fusion (LPBF) pose significant risks to the structural integrity of additively manufactured components. This paper introduces TransMatch, a nove…
Automatic Image Annotation (AIA) of AlmondNet-20 Method for Almond Detection by Improved CNN-based Model
Mohsen Asghari Ilani, Saba Moftakhar Tehran, Ashkan Kavei +1
In response to the burgeoning global demand for premium agricultural products, particularly within the competitive nut market, this paper introduces an innovative methodology aimed…
CNN-based Labelled Crack Detection for Image Annotation
Mohsen Asghari Ilani, Leila Amini, Hossein Karimi +1
Numerous image processing techniques (IPTs) have been employed to detect crack defects, offering an alternative to human-conducted onsite inspections. These IPTs manipulate images…