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Lightweight Deep Learning Models with Explainable AI for Early Alzheimer's Detection from Standard MRI Scans. [PDF]
Diagnostics (Basel)Sheikh F, Marouf AA, Rokne JG, Alhajj R.
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Enhancing fundus image analysis for diabetic retinopathy using CheXNet with CBAM and Grad-CAM visualization. [PDF]
Front Med (Lausanne)Al-Dolat W +10 more
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Explainable Deep Learning Framework for Binary Corrosion Image Classification Using Grad-CAM. [PDF]
Sensors (Basel)Aminudin MAI +5 more
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MobileDANet integrating transfer learning and dynamic attention for classifying multi target histopathology images with explainable AI. [PDF]
Sci RepS R SC, Rajaguru H.
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Perbandingan Arsitektur MobileNetV2 dan DenseNet121 untuk Klasifikasi
Jurnal Ilmiah Komputasiopenaire +1 more source
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Ultrasound Beamforming using MobileNetV2
2020 IEEE International Ultrasonics Symposium (IUS), 2020In the past few years, deep learning has disrupted several low-level medical imaging tasks such as reconstruction of Computed Tomography (CT) and Magnetic Resonance (MR) images. In this work, we propose a novel deep learning-based approach for the low-level task of ultrasound image reconstruction from the pre-beamformed channel data. More specifically,
Sobhan Goudarzi, Amir Asif, Hassan Rivaz
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Fire Detection using Deeplabv3+ with Mobilenetv2
2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021Fire detection is high priority task in the current decade, due to the high occurrences of fire in urban and forest area. Every year, millions of hectares of forests are burned and destroyed. The cost of dislocation could be optimized by implementing an accurate detection system.
Houda Harkat +2 more
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