Deep Convolutional Neural Network Based Covid-19 Classification From Radiology X-Ray Images For IoT Enabled Devices

Intelligent speech technologies for transcription, disease diagnosis, and medical equipment interactive control in smart hospitals: A review

“…However, researchers can continuously explore the potential of DL methods such as Attention-based LSTM [ 45 , 47 ], end-to-end models [ 134 ], and Transformer models [ 187 ] and try advanced recognition algorithms to improve the performance of IST for medical applications. Moreover, the fusion of voice signals with signals of other modalities such as electroacoustic gate signals, EMR, X-ray images, and ultrasound [ 4 , 5 ] will be more valuable for disease diagnosis in smart hospitals. For example, combining the chest X-ray images and cough sounds-based COVID-19 non-contact classification methods will minimize severity and mortality rates during the pandemic [ 5 , 6 , 188 , 189 ].…”

“…Moreover, the fusion of voice signals with signals of other modalities such as electroacoustic gate signals, EMR, X-ray images, and ultrasound [ 4 , 5 ] will be more valuable for disease diagnosis in smart hospitals. For example, combining the chest X-ray images and cough sounds-based COVID-19 non-contact classification methods will minimize severity and mortality rates during the pandemic [ 5 , 6 , 188 , 189 ]. Furthermore, algorithms in other domains can be used in speech signal processing, such as AlexNet, VGGNet, GoogLeNet, and ResNet in image recognition can be adopted in the spectrum of speech signals.…”

“…With the development of robotics and artificial intelligence (AI) technologies, machines can achieve more efficient and accurate disease diagnosis and assessment in some cases and replace nurses to assist patients in their lives, which alleviate the problem of insufficient medical resources. For example, intelligent image processing methods based on deep learning (DL) have been applied to processing X-ray, CT, ultrasound, and facial images for diagnosing diseases such as COVID-19 detection [ [4] , [5] , [6] ], paralysis assessment [ 7 , 8 ], and autism screening [ 9 ]. In addition, intelligent speech technology (IST) plays a critical role in smart hospitals because language is the most natural mean of communication between doctors and patients and contains much information, such as patients’ identity, age, emotion, and even symptoms of diseases [ 10 ].…”

Foreign Object Debris (FOD) Classification Through Material Recognition Using Deep Convolutional Neural Network With Focus on Metal

“…Deep Learning applications are vastly used in automatic recognition/ detection problems worldwide mostly in medical applications [2], [3], [4].…”

“…Furthermore, in contrast to the decades of research on object recognition, material recognition is a flourishing and challenging field. The two main approaches followed by scientists for material recognition are handcrafted and automatic feature extraction as shown in Fig 1 . Hand-crafted feature extraction further divides into surface reflectance [3], 3D texture [4], and feature fusion [5] approaches. All these approaches involve the collection of features from images through approaches like bidirectional reflectance distribution function Bidirectional Reflectance Distribution Function (BRDF) [6], Scale Invariant Feature Transform (SIFT) [7], Histogram of Gradient (HOG) [8], interest points [9], optical pyramids or optical flow [10].…”