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Build Edge AI Systems Using eFPGA Technology

Artificial-intelligence algorithms, particularly artificial neural networks and their hardware, are critical in addressing edge AI applications.

Artificial Intelligence Algorithms Detect Anemia from Fundus Images

The battle against potato black dot: A comprehensive review of two decades of research and management strategies

The battle against potato black dot: A comprehensive review of two decades of research and management strategies
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A COVID-19 X-ray image classification model based on an enhanced convo by Ashwini Kumar Pradhan, Debahuti Mishra et al

The classification of medical images is significant among researchers and physicians for the early identification and clinical treatment of many disorders. Though, traditional classifiers require more time and effort for feature extraction and reduction from images. To overcome this problem, there is a need for a new deep learning method known as Convolution Neural Network (CNN), which shows the high performance and self-learning capabilities. In this paper,to classify whether a chest X-ray (CXR) image shows pneumonia (Normal) or COVID-19 illness, a test-bed analysis has been carried out between pre-trained CNN models like Visual Geometry Group (VGG-16), VGG-19, Inception version 3 (INV3), Caps Net, DenseNet121, Residual Neural Network with 50 deep layers (ResNet50), Mobile-Net and proposed CNN classifier. It has been observed that, in terms of accuracy, the proposed CNN model appears to be potentially superior to others. Additionally, in order to increase the performance of the CNN cl

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