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Titlebook: Computer Vision and Image Processing; 5th International Co Satish Kumar Singh,Partha Roy,P. Nagabhushan Conference proceedings 2021 The Edi

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樓主: Taylor
51#
發(fā)表于 2025-3-30 10:31:14 | 只看該作者
Deep Neural Network for Pneumonia Detection Using Chest X-Rays,m abnormal regions (related to pneumonia). In our experiments, we achieve the highest accuracy of 99.13% using publicly available data: “Chest X-ray Images (Pneumonia)” [.]. The results outperformed handcrafted feature-based tools and other state-of-the-art works.
52#
發(fā)表于 2025-3-30 13:12:17 | 只看該作者
53#
發(fā)表于 2025-3-30 17:47:55 | 只看該作者
An Approach for Fraction of Vegetation Cover Estimation in Forest Above-Ground Biomass Assessment U been calculated from the Sentinel 2 image, namely: normalized difference vegetation index (NDVI), normalized difference index 45 (NDI45), and inverted red-edge chlorophyll index (IRECI). Then, the FVC images were generated from the above vegetation indices individually. The ground FVC values were e
54#
發(fā)表于 2025-3-30 23:15:16 | 只看該作者
Dynamic Multimodal Biometric System,sting, totally depends on the result of previously performed test. It will make very difficult for an imposter to fool the system. Three biometrics, Palm print, Knuckle print and Iris are collected in this system. The accuracy of the system is improved to 99.99% with respect to some earlier Models a
55#
發(fā)表于 2025-3-31 04:26:37 | 只看該作者
56#
發(fā)表于 2025-3-31 06:12:46 | 只看該作者
57#
發(fā)表于 2025-3-31 12:49:47 | 只看該作者
58#
發(fā)表于 2025-3-31 15:54:15 | 只看該作者
Automated Diagnosis of COVID-19 from CT Scans Based on Concatenation of Mobilenetv2 and ResNet50 Feding labels is used to train an SVM classifier to give the output. The proposed technique is validated on the benchmark COVID CT dataset comprising of a total of 2482 images with 1252 positive and 1230 negative cases. The experimental results reveal that the proposed feature fusion strategy achieves
59#
發(fā)表于 2025-3-31 19:52:19 | 只看該作者
60#
發(fā)表于 2025-4-1 01:38:22 | 只看該作者
The Web Server Gateway Interface (WSGI) been calculated from the Sentinel 2 image, namely: normalized difference vegetation index (NDVI), normalized difference index 45 (NDI45), and inverted red-edge chlorophyll index (IRECI). Then, the FVC images were generated from the above vegetation indices individually. The ground FVC values were e
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