A Survey Paper on AutoMate - A Smart Assistant

Abstract

Abstract: In the subject of intelligent transportation systems, autonomous vehicles are a prominent study issue because they have the potential to significantly reduce traffic and increase travel efficiency. One of the essential technologies for self-driving automobiles is scene classification, which serves as the foundation for these vehicles' decision-making. Deep learning-based approaches have shown promise in solving the scene classification problem in recent years. Nonetheless, there are a few issues with scene classification techniques that need more research, like how to handle similarities and contrasts within the same category. This paper proposes an enhanced deep network-based scene classification technique to address these issues. . In the subject of intelligent transportation systems, autonomous vehicles are a prominent study issue because they have the potential to significantly reduce traffic and increase travel efficiency. One of the essential technologies for self-driving automobiles is scene classification, which serves as the foundation for these vehicles' decision-making. Deep learning-based approaches have shown promise in solving the scene classification problem in recent years. Nonetheless, there are a few issues with scene classification techniques that need more research, like how to handle similarities and contrasts within the same category. This paper proposes an enhanced deep network-based scene classification technique to address these issues. . The experimental results show that the accuracy of the proposed method can reach which is higher than the state-of-the art methods