Lightweight Histological Tumor Classification Using a Joint Sparsity-Quantization Aware Training Framework

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Veröffentlicht in:IEEE Access Jg. 11; S. 119342 - 119351
Hauptverfasser: Dina Aboutahoun, Rami Zewail, Keiji Kimura, Mostafa I. Soliman
Format: Journal Article
Sprache:Japanisch
Veröffentlicht: Institute of Electrical and Electronics Engineers (IEEE) 01.01.2023
Schlagworte:
Algorithm
Applications of Deep Learning in Medical Imaging
Architectural engineering
Artificial intelligence
Cancer Imaging
Computer science
Deep Learning
Deep Learning in Medical Image Analysis
Electrical engineering. Electronics. Nuclear engineering
Engineering
Health Sciences
histopathology
Joint (building)
Machine learning
medical image analysis
Medicine
Operating system
Physical Sciences
Predictive Modeling
Process (computing)
pruning
quantization
Quantization (signal processing)
Radiology, Nuclear Medicine and Imaging
Radiomics in Medical Imaging Analysis
TK1-9971
transfer learning
Tumor Heterogeneity
ISSN:2169-3536
Online-Zugang:Volltext
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Beschreibung
ISSN:2169-3536
DOI:10.1109/access.2023.3327221