Blogger introduction : Teacher Huang Juhua is the author of the books "Introduction to Vue.js and Practical Mall Development" and "WeChat Mini Program Mall Development", CSDN blog expert, online education expert, CSDN diamond lecturer; specializes in graduation design education and tutoring for college students.
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1. Research background and significance
As a rare protected animal in my country, the Tibetan antelope's living conditions have always attracted much attention. However, because Tibetan antelopes are distributed in alpine and remote areas, traditional manual monitoring methods are not only costly and inefficient, but also difficult to cover a wide distribution area. Therefore, using modern technological means to realize automatic identification and detection of Tibetan antelopes is of great practical significance for protecting Tibetan antelopes and maintaining ecological balance.
The Tibetan antelope identification and detection system based on JAVA and Baidu AI is developed using the Springboot framework, which can realize automatic identification and detection of Tibetan antelope images. Through this system, conservation agencies can more easily obtain key data such as distribution information and population changes of Tibetan antelopes, providing strong support for formulating more scientific conservation strategies. At the same time, the research and implementation of this system will also help promote the application and development of JAVA technology and Baidu AI in the field of ecological protection.
2. Research status at home and abroad
At home and abroad, wildlife monitoring technology based on image recognition has been widely used and researched. Among them, some systems use different algorithms and models to achieve automatic identification and detection of a variety of wild animals.
Abroad, some well-known conservation agencies and scientific research institutions have developed highly automated and intelligent wildlife monitoring systems. These systems usually use advanced computer vision algorithms and deep learning models to achieve accurate recognition and real-time detection of wildlife images. At the same time, some open source wildlife identification systems have also been widely used and promoted, providing strong support for research and practice in related fields.
In China, with the continuous improvement of ecological protection awareness and the continuous development of technology, more and more conservation agencies have begun to pay attention to the research, development and application of wildlife monitoring technology. At present, some wildlife monitoring systems based on image recognition have been widely used and promoted in China. These systems are usually developed using programming languages such as JAVA and Python, and combine a variety of computer vision algorithms and deep learning models to achieve automatic identification and detection of wild animals. However, there are still relatively few identification and detection systems for specific rare protected animals such as Tibetan antelopes, and there are problems such as low recognition accuracy and poor real-time performance. Therefore, strengthening research and exploration in this field has important practical significance and application value. Through the design and implementation of the Tibetan antelope identification and detection system based on JAVA (Baidu AI), more efficient and accurate technical means and data support can be provided for the protection of Tibetan antelopes.
Research background and significance: Tibetan antelope is a rare wild animal unique to my country and has important ecological and scientific research value. However, due to factors such as the impact of human activities, illegal hunting, and habitat destruction, the Tibetan antelope faces serious threats to its survival, and its number has declined sharply. Therefore, carrying out research on the identification and detection of Tibetan antelopes has important scientific significance and conservation value.
Current research status at home and abroad: At present, some research on the identification and detection of Tibetan antelopes has been carried out at home and abroad. Among them, traditional methods mainly rely on manual analysis and recognition of images, but this method is time-consuming and labor-intensive and prone to misjudgment. In order to improve the accuracy and efficiency of recognition and detection, methods using artificial intelligence technology have been widely used in recent years.
Baidu AI provides a wealth of computer vision technologies and tools, providing a good foundation for the research and implementation of Tibetan antelope identification and detection. Among them, Baidu AI's image classification and target detection technology can enable computers to identify and detect images of Tibetan antelopes through training models, and provide corresponding results.
On this basis, this research will design and implement a Tibetan antelope recognition and detection system based on JAVA language and Springboot framework, using Baidu AI's image classification and target detection technology. The system can analyze and identify images uploaded by users, determine whether there are Tibetan antelopes in the images, and provide corresponding identification results and statistical information. The design and implementation of this system are of great significance and practical application value for protecting Tibetan antelopes, monitoring changes in wild animal population, and protecting the ecological environment.