《2022年考博英语-桂林理工大学考试题库及全真模拟冲刺卷（含答案带详解）套卷84》由会员分享，可在线阅读，更多相关《2022年考博英语-桂林理工大学考试题库及全真模拟冲刺卷（含答案带详解）套卷84（74页珍藏版）》请在金锄头文库上搜索。
1、2022年考博英语-桂林理工大学考试题库及全真模拟冲刺卷（含答案带详解）1. 单选题Human memory is notoriously unreliable. Even people with the sharpest facial-recognition skills can only remember so much.Its tough to quantify how good a person is at remembering. No one really knows how many different faces someone can recall, for example,
2、 but various estimates tend to hover in the thousandsbased on the number of acquaintances a person might have.Machines arent limited this way. Give the right computer a massive database of faces, and it can process what it seesthen recognize a face its told to findwith remarkable speed and precision
3、. This skill is what supports the enormous promise of facial-recognition software in the 21st century. Its also what makes contemporary surveillance systems so scary.The thing is, machines still have limitations when it comes to facial recognition. And scientists are only just beginning to understan
4、d what those constraints are. To begin to figure out how computers are struggling, researchers at the University of Washington created a massive database of facesthey call it MegaFaceand tested a variety of facial-recognition algorithms (算法) as they scaled up in complexity. The idea was to test the
5、machines on a database that included up to 1 million different images of nearly 700,000 different peopleand not just a large database featuring a relatively small number of different faces, more consistent with whats been used in other research.As the databases grew, machine accuracy dipped across t
6、he board. Algorithms that were right 95% of the time when they were dealing with a 13,000-image database, for example, were accurate about 70% of the time when confronted with 1 million images. Thats still pretty good, says one of the researchers, Ira Kemelmacher-Shlizerman. “Much better than we exp
7、ected,” she said.Machines also had difficulty adjusting for people who look a lot alikeeither doppelgangers (长相极相似的人), whom the machine would have trouble identifying as two separate people, or the same person who appeared in different photos at different ages or in different lighting, whom the mach
8、ine would incorrectly view as separate people.“Once we scale up, algorithms must be sensitive to tiny changes in identities and at the same time invariant to lighting, pose, age,” Kemelmacher-Shlizerman said.The trouble is, for many of the researchers whod like to design systems to address these cha
9、llenges, massive datasets for experimentation just dont existat least, not in formats that are accessible to academic researchers. Training sets like the ones Google and Facebook have are private. There are no public databases that contain millions of faces. MegaFaces creators say its the largest pu
10、blicly available facial-recognition dataset out there.“An ultimate face recognition algorithm should perform with billions of people in a dataset,” the researchers wrote.11. Compared with human memory, machines can_.12. Why did researchers create MegaFace?13. What does the passage say about machine
11、accuracy?14. What is said to be a shortcoming-of facial-recognition machines?15. What is the difficulty confronting researchers of facial-recognition machines?问题1选项A.identify human faces more efficientlyB.tell a friend from a mere acquaintanceC.store an unlimited number of human facesD.perceive imag
12、es invisible to the human eye问题2选项A.To enlarge the volume of the facial-recognition database.B.To increase the variety of facial-recognition software.C.To understand computers problems with facial recognition.D.To reduce the complexity of facial-recognition algorithms.问题3选项A.It falls short of resear
13、chers expectations.B.It improves with added computing power.C.It varies greatly with different algorithms.D.It decreases as the database size increases.问题4选项A.They cannot easily tell apart people with near-identical appearances.B.They have difficulty identifying changes in facial expressions.C.They
14、are not sensitive to minute changes in peoples mood.D.They have problems distinguishing people of the same age.问题5选项A.No computer is yet able to handle huge datasets of human faces.B.There do not exist public databases with sufficient face samples.C.There are no appropriate algorithms to process the
15、 face samples.D.They have trouble converting face datasets into the right format.【答案】第1题:A第2题:C第3题:D第4题:A第5题:B【解析】11.事实细节题。第一步，精准定位，定位到第三段第二句话Give the right computer a massive database of faces, and it can process what it seesthen recognize a face its told to findwith remarkable speed and precision“给计算机一个庞大的人脸数据库，它就可以处理它看到的东西，然后以惊人的速度和精度识别出它被要求寻找的人脸”，从这里可知答案选A选项“更有效地识别人脸”。B选项“把朋友和仅仅相识的人区别开来”，文章没有提及，属于无中生有；C选项“存储无限数量的人脸”，文章没有提及，属于无中生有；D选项“感知人眼看不见的图像”，文章没有提及，属于无中生有。12.事实细节题。第一步，精准定位，定位到文章第四段第一、三句话The thing is, machines still have limitations when it comes to facial recognitionTo begin to fi
