RESEARCH ON ROAD SURFACE CRACK DETECTION BASED ON SEGNET NETWORK

Abstract To enhance the precision and reliability of road crack detection, this study introduces an innovative neural network architecture.Strategies were implemented to effectively address the issue of overfitting Torque Spanner Set resulting from the intricacy of the proposed SegCrackNet.Dropout layers, multi-level output fusion, and T-bridge blo

Objective: The study aims to evaluate the association of metabolic syndrome and its components with bladder carcinoma.Methods: Study conducted in Department of Urology, Sheikh Zayed Hospital, Rahim Yar khan from August 2021 to November 2023.A total of 139 study subjects aged between 20 to 80 years, histopathologically confirmed cases of bladder car