ملخص البحث :

The accurate diagnosis of Alzheimer’s disease (AD) plays an important role in patient treatment, especially at the disease’s early stages, because risk awareness allows the patients to undergo preventive measures even before the occurrence of irreversible brain damage. Although many recent studies have used computers to diagnose AD, most machine detection methods are limited by congenital observations. AD can be diagnosed-but not predicted-at its early stages, as prediction is only applicable before the disease manifests itself. Deep Learning (DL) has become a common technique for the early diagnosis of AD. Here, we briefly review some of the important literature on AD and explore how DL can help researchers diagnose the disease at its early stages.

ملخص البحث :

Detecting concealed weapon underneath a person's clothing is important for public safety in places such as airports. The success rate of our proposed approach in detecting concealed weapons based on fused images is higher than that of the bag-of-features approach. Our approach uses a traditional discrete wavelet transform with hybrid bag-of-words to obtain fused imagery. We then utilized convolutional neural network (CNN) with a pre-trained CNN model using the CNN features of the fused image to train a multiclass SVM classifier. Our approach works well with X-ray images. The experimental results indicate the efficiency of the proposed hybrid approach.