BEST FINAL YEAR MATLAB PROJECT CENTER IN CHENNAI

                   

  

                         Chest X-ray images play a crucial role in pneumonia diagnosis, with deep transfer learning being a widely adopted method for pneumonia detection. However, effectively handling feature data extracted from deep models without succumbing to the challenges of feature dimensionality remains a formidable task. In response to this complex issue, we propose a novel two-stage deep feature selection (FS) method utilizing the voting differential evolution (VDE) algorithm. In this approach, a dimension adaptive search strategy is meticulously devised to ensure robust feature selection while concurrently reducing the dimension. To expedite the optimization process, we devise a CR adaptive adjustment method to enhance the efficiency of the algorithm