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As missing children age， they outgrow their last known photographs， which makes finding them tough. Now AI（Artificial Intelligence） could make it quicker to match any found children to those old photos.
Police can use software to age photos of people who have been missing for a while， but it tends to work best in adults， as age?related changes of adult faces are more predictable and so easier to make.
With children， these aged images dont tend to resemble the older children， and matching photos of found children to old images in a database of missing children is difficult. “Even with a recent face image of a child， it is extremely hard for a human to recognize， visually， who the child is from a large data set of child face images，” says Debayan Deb at Michigan State University.
Now Deb and his colleagues have created an algorithm（算法） to do this for them. They created a face?recognition algorithm on data sets， which contain images of nearly 1，000 children between 2 and 18 years old. Each was photographed at least four times over a period of six years.
AI learned to match recent photographs of children with images taken 2.5 years earlier 80 percent of the time.
With one year between the two photographs， the method was 90 percent accurate at recognizing faces. This dropped to 73 percent after three years. The approach beats comparing children with photos taken when they were aged 0 to 4 that have been aged by software， which stays at 50 percent recognition after six months. The new AI might help to improve accuracy of this kind of software as well.
Debs next goal is to make the age gap wider. His team also hopes to develop an app that could be used to fight child trafficking.
1. What is suggested in the first paragraph？
A. Found children change greatly.
B. The old photos are hard to read.
C. Childrens face changes are unpredictable.
D. Photos of children are easy to match.
2. Why do Debs team do the research？
A. To help the police change their software.
B. To prove the advantages of AI function.
C. To build a database to find the missing children.
D. To improve the accuracy of childrens face?recognition.
3. What does the underlined word “trafficking” in the last paragraph mean？
A. Comparing.
B. Illegal trade.
C. Recognizing.
D. Image matching.
4. What is the main idea of the text？
A. AI helps to find missing kids by old photos.
B. Age?related changes of faces are predictable.
C. A face?recognition algorithm has been created.
D. A new software is improved to find missing kids.
Difficult sentence
The approach beats comparing children with photos taken when they were aged 0 to 4 that have been aged by software， which stays at 50 percent recognition after six months.
【翻译】
【点石成金】这是一个主从复合句，The approach beats comparing children with photos taken...
by software是主句，when they were aged 0 to 4是连词when引导的时间状语从句，that have been aged by software是关系代词that引导的限制性定语从句，which stays at 50 percent recognition after six months是关系代词which引导的非限制性定语从句。
Police can use software to age photos of people who have been missing for a while， but it tends to work best in adults， as age?related changes of adult faces are more predictable and so easier to make.
With children， these aged images dont tend to resemble the older children， and matching photos of found children to old images in a database of missing children is difficult. “Even with a recent face image of a child， it is extremely hard for a human to recognize， visually， who the child is from a large data set of child face images，” says Debayan Deb at Michigan State University.
Now Deb and his colleagues have created an algorithm（算法） to do this for them. They created a face?recognition algorithm on data sets， which contain images of nearly 1，000 children between 2 and 18 years old. Each was photographed at least four times over a period of six years.
AI learned to match recent photographs of children with images taken 2.5 years earlier 80 percent of the time.
With one year between the two photographs， the method was 90 percent accurate at recognizing faces. This dropped to 73 percent after three years. The approach beats comparing children with photos taken when they were aged 0 to 4 that have been aged by software， which stays at 50 percent recognition after six months. The new AI might help to improve accuracy of this kind of software as well.
Debs next goal is to make the age gap wider. His team also hopes to develop an app that could be used to fight child trafficking.
1. What is suggested in the first paragraph？
A. Found children change greatly.
B. The old photos are hard to read.
C. Childrens face changes are unpredictable.
D. Photos of children are easy to match.
2. Why do Debs team do the research？
A. To help the police change their software.
B. To prove the advantages of AI function.
C. To build a database to find the missing children.
D. To improve the accuracy of childrens face?recognition.
3. What does the underlined word “trafficking” in the last paragraph mean？
A. Comparing.
B. Illegal trade.
C. Recognizing.
D. Image matching.
4. What is the main idea of the text？
A. AI helps to find missing kids by old photos.
B. Age?related changes of faces are predictable.
C. A face?recognition algorithm has been created.
D. A new software is improved to find missing kids.
Difficult sentence
The approach beats comparing children with photos taken when they were aged 0 to 4 that have been aged by software， which stays at 50 percent recognition after six months.
【翻译】
【点石成金】这是一个主从复合句，The approach beats comparing children with photos taken...
by software是主句，when they were aged 0 to 4是连词when引导的时间状语从句，that have been aged by software是关系代词that引导的限制性定语从句，which stays at 50 percent recognition after six months是关系代词which引导的非限制性定语从句。