大学英语六级仔细阅读专项强化真题试卷2
仔细阅读
Human memory is notoriously unreliable. Even people with the sharpest facial-recognition skills can only remember so much.
It\’ s tough to quantify how good a person is at remembering. No one really knows how many different faces someone can recall, for example, but various estimates tend to hover in the thousands—based on the number of acquaintances a person might have.
Machines aren\’ t limited this way. Give the right computer a massive database of faces, and it can process what it sees—then recognize a face it\’ s told to find—with remarkable speed and precision. This skill is what supports the enormous promise of facial-recognition software in the 21st century. It\’ s 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 understand what those constraints are. To begin to figure out how computers are struggling, researchers at the University of Washington created a massive database of faces—they call it MegaFace—and tested a variety of facial-recognition algorithms (算法) as they scaled up in complexity. The idea was to test the machines on a database that included up to 1 million different images of nearly 700,000 different people—and not just a large database featuring a relatively small number of different faces, more consistent with what\’s been used in other research.
As the databases grew, machine accuracy dipped across the 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. That\’ s still pretty good, says one of the researchers, Ira Kemelmacher-Shlizerman. \\
1.Compared with human memory, machines can______.(C)
A. identify human faces more efficiently
B. tell a friend from a mere acquaintance
C. store an unlimited number of human faces
D. perceive images invisible to the human eye
解析：细节题。原文第一、二段指出，人的记忆是不可靠的，能记住的面孔也有限。第三段第一句话指出，机器不受这方面的限制。由此可知，机器可以储存的人脸图像是无限的，故答案为C。B、D两项原文均未提及，故排除。A项与原文不符，文中只是说给电脑输入一个庞大的人脸数据库，它能够以不可思议的速度和精确度识别出要求它识别的面孔，并没有和人进行比较，故排除。
2.Why did researchers create MegaFace?(C)
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.
解析：细节题。原文第四段第三句话指出，为了找出电脑识别人脸的困难所在，华盛顿大学的研究人员创造了一个他们称之为MegaFace的巨大的人脸数据库，通过增加复杂性来测试各种人脸识别算法。由此可知，研究人员创造MegaFace的目的是为了发现电脑在人脸识别时可能犯的错误，即存在的一些问题，故答案为C。A项答非所问，这并不是创造MegaFace的目的，故排除。B、D两项原文均未提及，故排除。
3.What does the passage say about machine accuracy?(D)
A. It falls short of researchers’ expectations.
B. It improves with added computing power.
C. It varies greatly with different algorithms.
D. It decreases as the database size increases.
解析：细节题。原文第五段第一句话指出，随着数据库的不断扩大，机器整体的准确性在下降。由此可知，数据库扩大，机器的准确性就会降低，故答案为D。A项与原文不符，原文第五段最后两句话提到，研究人员称，这比她们预期的要好，并不是没有达到研究人员的预期，故排除。B、C两项原文均未提及，故排除。
4.What is said to be a shortcoming of facial-recognition machines?(A)
A. They cannot easily tell apart people with near-identical appearances.
B. They have dif
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