[背景提升]從“帝國理工”到美國名校，學霸的科研體會

本文標題：從“帝國理工”到美國名校，學霸的科研體會，如今留學的人越來越多，不論高中生、大學生還是讀研的學生，都想早日去留學接受好的教育，很多同學對美國名?？蒲?美國留學中介,美國留學條件,美國留學網(wǎng),美國留學申請，美國研究生留學的相關(guān)問題有所疑問，下面澳際小編整理了《[背景提升]從“帝國理工”到美國名校，學霸的科研體會》，歡迎閱讀，如有疑問歡迎聯(lián)系我們的在線老師，進行一對一答疑。

　　帝國理工學院, 1907年建立于英國倫敦，在國際學術(shù)界有著頂級聲望，在各類權(quán)威榜單中排名穩(wěn)居世界前十。又與劍橋大學、牛津大學、倫敦大學學院、倫敦政治經(jīng)濟學院并稱為“G5超級精英大學”，研究水平被公認為英國大學的前五強之列，尤其以工程專業(yè)而著名。在帝國的相關(guān)人物中，共有14位諾貝爾獎獲得者和3位菲爾茲獎獲得者。

　　本文作者H同學，品學兼優(yōu)，目前是帝國理工學院，二年級學生。

　　H同學有更高的夢想，希望本科畢業(yè)后能夠到美國最好的大學讀研究生。為此，參與了名校科研項目，增加學術(shù)背景，開拓視野，獲得真知。

　　本文是學生在美國大學科研學習結(jié)束后所寫的感受，供學生及家長參考。

　　Final Report for the Summer Research

　　注：中文譯文是編輯進行的整理，英語能力較好的學生和家長建議直接閱讀英文。

　　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.

　　幸運的是，在這個夏天，我有機會在美國做暑期研究。我加入的實驗室被稱為計算機科學人工智能實驗室，它是世界上機器學習的頂尖研究中心。

　　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.

　　在確定主題之后，我首先要做的是使用OpenCV庫來進行撲克檢測，但是，我?guī)缀鯖]有關(guān)于Python的編碼體驗，所以我必須看YouTube上關(guān)于在Python中使用OpenCV的教程。經(jīng)過幾天的斗爭，我用特征檢測來捕捉撲克的數(shù)量和類型，修正檢測的準確性相當高。缺點之一是檢測真正需要黑色背景。

　　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興趣的話題。最后，我決定讓人工智能自動玩德克薩斯HORD撲克(像著名的Alpha Go)，其中一個難點是如何選擇合適的模型。

　　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.

　　經(jīng)檢測已經(jīng)完成，我所討論的A教授，而且，她給我用隨機森林或決策樹構(gòu)建模型的建議。主要問題是數(shù)據(jù)采集。由于互聯(lián)網(wǎng)上的數(shù)據(jù)很難解讀，為整個戰(zhàn)役中有用的數(shù)據(jù)太少用。這種情況可能為深入學習造成較大偏差問題。有一個交替的方法來找到數(shù)據(jù)，這是建筑的游戲，由職業(yè)球員和機器玩，如α方法去發(fā)展。這種方法似乎是可行的，但是，有兩個困難不可克服的短時間內(nèi)。一是沒有專業(yè)的球員，我知道在那個時間。另外，我也沒有讓德克薩斯撲克游戲體驗，幾乎沒有可能對我來說3周建立單獨的游戲。

　　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，我選擇放棄德克薩斯撲克項目。然后我試著改變我對計算機視覺的興趣。那時候，一個比賽的比賽吸引了我的目光。競爭是關(guān)于VR對象識別和對象之間的關(guān)系。前一種是利用卷積神經(jīng)網(wǎng)絡建立成熟的技術(shù)來獲得正確的位置和識別，然而，這些關(guān)系對我來說是非常有趣的。

　　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，我必須用一個星期來建立神經(jīng)網(wǎng)絡，并改變模型的參數(shù)，并花了幾乎其他星期來決定模型的關(guān)系部分。隨機森林可能相當適合這個項目。最后，我編寫了培訓模式的框架。

　　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.

　　總而言之，我從研究經(jīng)驗中學到的最重要的東西之一是科學的精神，A教授不僅僅教會了我很多關(guān)于學術(shù)知識的知識，也教會了我努力工作和思考的精神，勇于創(chuàng)造也是另一回事。我在后一輩子總是會提醒自己的。

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