For years, Mark Hager worked as an at-sea fishery observer, going out on New English fishing boats for days or weeks and keeping detailed records of every fish caught or thrown back. The work could be perilous: on one trip, a boat turned sideways in 20-foot seas, and Hager and the crew put on survival suits in case they had to jump overboard. But the counting was essential to protecting the ecosystem.
In the early 2000s, the fishing industry began fixing video. cameras on boats, so that humans could track the data from ashore. In 2019, Hager and the Gulf of Maine Research Institute launched a company, New England Marine Monitoring, based in. Portland, Maine, to provide technology support for ships using electronic monitoring. His team has to watch hours of video footage (镜头), look for each moment when a fish is discarded (丢弃), and then make a note of the species and the time it was discarded. In ten hours of video, there might be 45 minutes between each case of a discarded fish
When Hager consulted with other scientists, they came up with a new idea. Now Hager and his team are using their notes as training data for an artificial intelligence (AI) algorithm (算法) —programming the AI to scan the video footage and indicate points of interest along the time line for a human to look through. “Instead of ten hours of video, we’ll be able to look at about 100 pictures, which we can do in about 20 minutes.” Hager says.
The result could save time and money, but Hager has a bigger goal. He wants to prove that AI algorithms can be used to count every fish that’s caught and discarded. To be effective, the algorithm will need to be able to identify the total volume of a fish haul (一网鱼的量), count containers of fish, and potentially even count and measure individual fish. Using video monitoring to count a small amount of the total catch is one thing. Using it to count the entire haul on a ship is a huge challenge—one that has never been achieved before.
【小题1】What does the underlined word “perilous” in Paragraph one probably mean?| A．Well-paid | B．Time-consuming |
| C．Eye-catching | D．Risk-taking |
| A．The cost is usually quite high. | B．The process is slow and boring. |
| C．The result is not always correct. | D．The quality of images is poor. |
| A．Al algorithm can be of great help. |
| B．Pictures work better than videos. |
| C．Humans are more dependable than cameras. |
| D．Interest plays a key role in the fishing industry. |
| A．To encourage readers to protect the ecosystem. |
| B．To introduce a newly-founded fishing company. |
| C．To report the influence of technology on fishing. |
| D．To talk about the life of an at-sea fishery observer. |
