Technological innovation: With the continuous development and innovation of deep learning, neural network and other technologies, the performance and ability of computer vision will continue to improve, making it possible to solve more complex visual tasks.
Application scenario expansion: Computer vision technology will be applied to more fields and scenarios, such as automatic driving, medical image analysis, intelligent monitoring, virtual reality, augmented reality and so on.
Interdisciplinary integration: Computer vision will be integrated with other artificial intelligence fields (such as natural language processing and speech recognition). ) and other disciplines provide new ideas and methods for solving complex problems.
Personalization and intelligence: Computer vision system will be more personalized and intelligent, and can provide customized solutions according to different users' needs and scenarios.
Real-time low power consumption: Computer vision technology will make a breakthrough in real-time low power consumption to meet the needs of mobile devices, Internet of Things and other applications.
Data security and privacy protection: Computer vision technology needs to deal with a large number of image and video data in the application process. How to achieve efficient visual tasks under the premise of ensuring data security and privacy will become an important topic.
Interpretability and reliability: More attention will be paid to the interpretability and reliability of computer vision system to improve users' trust and satisfaction with the system.
In a word, computer vision, as a developing field, has great prospects and potential. With the development of technology and application, computer vision will play an increasingly important role in various fields.