• Dr.K.Sree rama Murthy
• Dr.K.Kranthi Kumar
• B.Neha
• G.Praveena
• S.Sahithi

Organizations that have acquired strategic knowledge are now widely used in powerful medical photo classification pipelines.international research aims to improve prediction performance by combining different models and predictions. However, it is necessary to consider how well and in which areas general learning methods are suitable for deep clinical picture-based pipelines. These studies proposed a pipeline of reproducible clinical imaging categories to explore the impact of international research strategies such as augmentation, stacking and bagging. The pipeline consists of advanced image development and preprocessing techniques and nine deep convolutional neural community topologies. This study was performed using four commonly used scientific image datasets of varying complexity.

AN ANALYSIS ON ENSEMBLE LEARNING OPTIMIZED MEDICAL IMAGE CLASSIFICATION WITH DEEP LEARNING ALGORITHMS

"AN ANALYSIS ON ENSEMBLE LEARNING OPTIMIZED MEDICAL IMAGE CLASSIFICATION WITH DEEP LEARNING ALGORITHMS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.n204-n207, May-2023, Available :http://www.jetir.org/papers/JETIR2305D35.pdf

"AN ANALYSIS ON ENSEMBLE LEARNING OPTIMIZED MEDICAL IMAGE CLASSIFICATION WITH DEEP LEARNING ALGORITHMS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppn204-n207, May-2023, Available at : http://www.jetir.org/papers/JETIR2305D35.pdf