Breast cancer is a global health concern, and early detection through screening programs is crucial for reducing mortality. Deep Convolutional Neural Networks (CNNs) are widely adopted for image classification, but their accuracy depends on the number of layers, structure paramet…
A non-invasive brain-computer interface is an innovative approach to a control device without physical execution. Electroen-cephalography (EEG) is the key for these applications. However, classifying EEG signals using fewer computational models is challenging for these applicatio…
Accurate and efficient classification of bone fractures from X-ray images is crucial for timely diagnosis, effective treatment planning, and improved patient outcomes in orthopedic medicine. Convolutional neural networks (CNNs) have demonstrated their ability to automatically ext…
Fabric defects can significantly impact the quality of a textile product. By analyzing the types and frequencies of defects, manufacturers can identify process inefficiencies, equipment malfunctions, or operator errors. Although deep learning networks are accurate in classificati…
Object detection is one of the cutting-edge tools of computer vision to present the content of an image or video frame. Object recognition describes the entire scene in the frame. So many sophisticated algorithms are available to detect and recognize the object in the frame. The…
Physical issues started to receive more attention due to the sedentary lifestyle prevalent in modern culture. The Ten Meter Walk Test allows measuring the person's capacity to walk along 10 m and analyzing the advancement of various medical procedures for ailments, including stro…
Mobile users can use a mobile sensor to record ECG data, and on-device ECG classification can provide a more efficient diagnosis than standard care. Deep Neural Networks (DNNs) have excelled in artificial intelligence (AI)-based applications to extract patterns from the complex w…