LungVision: X-ray Imagery Classification for On-Edge Diagnosis Applications
This study presents a comprehensive analysis of utilizing TensorFlow Lite on mobile phones for the on-edge medical diagnosis of lung diseases. This paper focuses on the technical deployment of various deep learning architectures to classify nine respiratory system diseases using X-ray imagery. We pr...
محفوظ في:
| المؤلف الرئيسي: | Aldamani, Raghad (author) |
|---|---|
| مؤلفون آخرون: | Abuhani, Diaa Addeen (author), Shanableh, Tamer (author) |
| التنسيق: | article |
| منشور في: |
2024
|
| الموضوعات: | |
| الوصول للمادة أونلاين: | https://hdl.handle.net/11073/25544 |
| الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
مواد مشابهة
-
Edge-Optimized Deep Learning Architectures for Classification of Agricultural Insects with Mobile Deployment
حسب: Akhtar, Muhammad Hannan
منشور في: (2025) -
An IoT System Using Deep Learning to Classify Camera Trap Images on the Edge
حسب: Zaulkernan, Imran
منشور في: (2022) -
Analysing Pneumonia Disease Depending on X-Ray Images of Chest Using Deep Learning
حسب: Khamees, Ahmed
منشور في: (2023) -
A Two-Tier Post-Processing Framework for Lightweight Video Anomaly Detection
حسب: Akhtar, Muhammad Hannan
منشور في: (2025) -
DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins
حسب: Samir Brahim, Belhaouari
منشور في: (2025)