The success of deep learning methods over the past decade has been partially shrouded in the shadow of adversarial attacks. Even a tiny undetectable deformation can lead to vicious misleading targeted at safety-critical applications. In contrast, the...
Data-driven methods have transformed our ability to assess and respond to human movement with wearable robots, promising real-world rehabilitation and augmentation benefits. However, the proliferation of data-driven methods, with the associated deman...
Crime is a critical social issue that threatens public safety, and accurately predicting and reducing crime in hotspot areas is a key objective. Crime patterns are inherently complex, with substantial spatial and temporal variability, which makes acc...
Correct histopathological image classification of lung and colon cancer is a stringent challenge for clinical pathology. This work introduces a hybrid deep learning network by combining traditional handcrafted features of LBP, GLCM, wavelet, color, a...
Neural network models for outcome prediction play a pivotal role in neurological disease research, particularly for baseline risk assessment. Schizophrenia, a complex and relatively rare neuropsychiatric disorder, presents significant diagnostic chal...
Deep learning tools based on computer vision have emerged as alternative methods for assessing radiographic image patterns. These approaches have been explored for various forensic applications, including sex and age estimation. This study aimed to e...
Among the various sports activities that are carried out all over the world, football is undoubtedly the most popular, most participated in and most watched activity and sport. The increasing spread of sports has caused it to break down geographical,...
Cancer remains one of the leading causes of global mortality, with lung, colon, skin, and breast cancers contributing significantly to the disease burden. Accurate and timely classification of histopathological images is critical for effective diagno...
Breast cancer is a major global health issue in women, where diagnosis at an early stage is decisive for enhancing the effectiveness of treatment and survival. Despite the advances in imaging using medical technologies, maintaining uniformly good dia...
Neonatal respiratory monitoring is crucial for assessing breathing patterns, but the lack of real-time clinical data limits the development of machine learning (ML) models. This study provides a synthetic signal generation framework to replicate infa...
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