从“帝国理工”到美国名校，学霸的科研体会

　　帝国理工学院, 1907年建立于英国伦敦，在国际学术界有着顶级声望，在各类权威榜单中排名稳居世界前十。又与剑桥大学、牛津大学、伦敦大学学院、伦敦政治经济学院并称为“G5超级精英大学”，研究水平被公认为英国大学的前五强之列，尤其以工程专业而著名。在帝国的相关人物中，共有14位诺贝尔奖获得者和3位菲尔兹奖获得者。

　　本文作者H同学，品学兼优，目前是帝国理工学院，二年级学生。

　　H同学有更高的梦想，希望本科毕业后能够到美国最好的大学读研究生。为此，参与了名校科研项目，增加学术背景，开拓视野，获得真知。

　　本文是学生在美国大学科研学习结束后所写的感受，供学生及家长参考。

　　Final Report for the Summer Research

　　注：中文译文是编辑进行的整理，英语能力较好的学生和家长建议直接阅读英文。

　　In this summer, fortunately, I have a chance to do summer research in US. The lab which I have joined is called computer science artificial intelligence lab, which is the top research center for machine learning in the world.

　　幸运的是，在这个夏天，我有机会在美国做暑期研究。我加入的实验室被称为计算机科学人工智能实验室，它是世界上机器学习的顶尖研究中心。

　　In the first week, I have searched a large amount of the information in order to locate the topic which might attract my interests. Finally, I have decided to make the artificial intelligence for automatically playing the Texas Hold’em poker (like the famous alpha go) one of the difficulties is that how to choose the suitable models.

　　在确定主题之后，我首先要做的是使用OpenCV库来进行扑克检测，但是，我几乎没有关于Python的编码体验，所以我必须看YouTube上关于在Python中使用OpenCV的教程。经过几天的斗争，我用特征检测来捕捉扑克的数量和类型，修正检测的准确性相当高。缺点之一是检测真正需要黑色背景。

　　After the topic has been determined, first thing which I have to do is using the OpenCV library to make the poker detection, however, I have almost no coding experience on python, so I have to watch the tutorial on YouTube about using OpenCV in python. After few days of struggle, I used the feature detection to capture the number and type of pokers, the accuracy of correcting detection is pretty high. One of the disadvantages is the detection truly need the black background.

　　在第一周，我搜索了大量的信息，以便找到可能吸引我兴趣的话题。最后，我决定让人工智能自动玩德克萨斯HORD扑克(像著名的Alpha Go)，其中一个难点是如何选择合适的模型。

　　After the detection has been finished, I discussed with the Prof A, and, she gives me the advice of using the random forest or the decision trees to build the models. Then the major problems become the data collecting. Due to the data on the internet are hard to decode, and useful data for the whole battle were too less to use. This situation might lead to a large bias problem for the deep learning. There is one alternating method to find the data, which were building the game and played by the professional player and machine, like the development method of alpha go. This method seems possible, however, there were two difficulties which might not be overcome during the short time. One is there is no professional player who I knew at that time. The other is that I also had no experience of making the Texas Hold’em poker game, and there is almost no possible for me to build the game alone for three weeks.

　　经检测已经完成，我所讨论的A教授，而且，她给我用随机森林或决策树构建模型的建议。主要问题是数据采集。由于互联网上的数据很难解读，为整个战役中有用的数据太少用。这种情况可能为深入学习造成较大偏差问题。有一个交替的方法来找到数据，这是建筑的游戏，由职业球员和机器玩，如α方法去发展。这种方法似乎是可行的，但是，有两个困难不可克服的短时间内。一是没有专业的球员，我知道在那个时间。另外，我也没有让德克萨斯扑克游戏体验，几乎没有可能对我来说3周建立单独的游戏。

　　Unfortunately, I chose to give up the project of Texas Hold’em poker. Then I had tried to change my interests in the computer vision. At that time, one of the competitions on the Kaggle has attracted my sights. The competition is about the VR object recognition and relationships between objects. The previous one which has been building the mature techniques to get the right position and recognition by using the convolution neural networks, nevertheless, the relationships are quite interesting for me to do the research on this aspect.

　　不幸的是，我选择放弃德克萨斯扑克项目。然后我试着改变我对计算机视觉的兴趣。那时候，一个比赛的比赛吸引了我的目光。竞争是关于VR对象识别和对象之间的关系。前一种是利用卷积神经网络建立成熟的技术来获得正确的位置和识别，然而，这些关系对我来说是非常有趣的。

　　So, first I have to use a week to build the neural network and change the parameters of the model and spent almost other weeks to decide the models for relationship parts. The random forest might be quite suitable for this project. Finally, I have written the frame of the training models.

　　所以，首先，我必须用一个星期来建立神经网络，并改变模型的参数，并花了几乎其他星期来决定模型的关系部分。随机森林可能相当适合这个项目。最后，我编写了培训模式的框架。

　　To be conclude, one of the most significant things which I have learnt from the research experience is the mental of science, Prof. A has taught me a lot about not only about the academic knowledges but also the mental of hard working and thinking differently, braving creating is also another mental which I would always remind myself in the latter life.

　　总而言之，我从研究经验中学到的最重要的东西之一是科学的精神，A教授不仅仅教会了我很多关于学术知识的知识，也教会了我努力工作和思考的精神，勇于创造也是另一回事。我在后一辈子总是会提醒自己的。