Gastro Intestinal Disease Classification Using Hierarchical Spatio Pyramid TranfoNet With PitTree Fusion and Efficient-CondConv SwishNet

Early detection of Gastrointestinal (GI) tract diseases is essential for effective healthcare management, treatment, and prevention, ultimately lowering morbidity and mortality rates worldwide. Current classification models lack spatial feature arrangement consideration, diminishing discriminative p...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE access 2024, Vol.12, p.113972-113987
Hauptverfasser:	Sharmila, V., Geetha, S.
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Algorithms Classification Convolutional neural networks Deep learning Disease Diseases Dyed lifted polyps dyed resection margins Endoscopes Endoscopy Feature extraction Gastrointestinal tract gastrointestinal tract disease grad-CAM Graph theory Image enhancement Medical imaging minimum spanning tree Pattern analysis spatial transformer swish activation Tumors Ulcerative colitis Visual discrimination
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!