Quality assessment in industrial applications is often carried out through visual inspection,
usually performed or supported by human domain experts. However, the manual visual …

Ensemble multifeatured deep learning methodology has emerged as a powerful approach
to overcome the limitations of single deep learning models in terms of generalization …

The occurrence of faults in textile manufacturing methods results in major wastage of the
properties. Additionally, it also affects the quality of the fabric products. Manual inspection …

Detecting brain tumours is complex due to the natural variation in their location, shape, and
intensity in images. While having accurate detection and segmentation of brain tumours …

Defective components within solar photovoltaic (PV) arrays overheat, resulting in particular
temperature patterns under the long-wave thermal infrared (LWIR) spectrum. The detection …

Traditional vision methods for solar cell defect detection have problems such as low
accuracy and few types of detection, so this paper proposes an optimized YOLOv5 model for …

One of the challenges in the field of photovoltaics (PV) is the automation of defect detection
in electroluminescent (EL) images of PV cells. This is due to the similarities between defects …

Solar photovoltaic technology can be regarded as a safe energy generation system with
relatively less pollution, noiseless, and abundant solar source. The operation and …

This research paper presents a comprehensive study on the development and evaluation of
a brain tumor classification model using advanced image processing and deep learning …

Fabric defects can significantly impact the quality of a textile product. By analyzing the types
and frequencies of defects, manufacturers can identify process inefficiencies, equipment …