Fusion: Practice and Applications FPA 2692-4048 2770-0070 10.54216/FPA https://www.americaspg.com/journals/show/3226 2018 2018 Dept. of Electrical Engineering, Benha Faculty of Engineering, Benha University, Benha, Egypt. Bahaa Bahaa Dept. of Electrical Engineering, Benha Faculty of Engineering, Benha University, Benha, Egypt. Ayman S. Selmy Dept. of Electrical Engineering, Benha Faculty of Engineering, Benha University, Benha, Egypt Wael A. Mohamed Machine- and deep-learning techniques have been used in numerous real-world applications. One of the famous deep-learning methodologies is the Deep Convolutional Neural Network. AlexNet is a well-known global deep convolutional neural network architecture. AlexNet significantly contributes to solving different classification problems in different applications based on deep learning. Therefore, it is necessary to continuously improve the model to enhance its performance. This survey study formally defined the AlexNet architecture, presented information on current improvement solutions, and reviewed applications based on AlexNet improvements. This work also presents a simple survey based on a fusion of AlexNet with different machine-learning techniques for recent research in biomedical applications. In the survey results for about 11 research papers for both improvement and fusion techniques of AlexNet, it was clear that the fusion was the superior one with 99.72, and the improved one was 99.7%. In the conclusion and discussion section, there was a comparison between the improved techniques and fusion techniques of AlexNet and a proposal for future work on AlexNet development. 2025 2025 123 146 10.54216/FPA.170210 https://www.americaspg.com/articleinfo/3/show/3226