This study explored the application of CNN-Transfer Learning for nondestructive chicken
egg fertility detection for precision poultry hatchery practices. Four models, VGG16 …

The research presented in this paper aims at egg fertility detection during incubation based
on the presence of the embryo. To obtain an optimal detection method that does not …

Medical image segmentation is an essential process in disease analysis and diagnosis, in
which medical images are divided into specific areas of anatomic or pathological structures …

This research aims to improve the performance of convolutional neural network (CNN) in
medical image segmentation that will detect specific parts of the body's anatomical …

Optical coherence tomography angiography (OCTA) is a non-invasive ophthalmic imaging
modality that is widely used in clinical practice. Recent technological advances in OCTA …

This study aims to identify chicken eggs fertility using the support vector machine (SVM)
classifier method. The classification basis used the first-order statistical (FOS) parameters as …

This study aims to classify the maturity level of oil palm using the K-Nearest Neighbors
(KNN) method based on the extraction of RGB and L* a* b color features. This classification …

This study systematically investigates the impact of image enhancement techniques on
Convolutional Neural Network (CNN)-based Brain Tumor Segmentation, focusing on …

The quality of the hatching process influences the success of the hatch rate besides the
inherent egg factors. Eliminating infertile or dead eggs and monitoring embryonic growth are …

This study aims to identify chicken egg embryos with the concept of image processing. This
concept uses input and output in images. Thus the identification process, which was …