If you've ever wondered what makes the perfect selfie, some of the world's most powerful computers have been pondering the same question.

如果你在琢磨怎樣自拍更好看，世界上最強(qiáng)大的電腦也在思考著同樣的問題。

Researchers have trained a neural network designed to think like the human brain to analyse millions of selfies to find what works.

研究者訓(xùn)練設(shè)計(jì)的神經(jīng)網(wǎng)絡(luò)像人類那樣思考，以分析數(shù)百萬張自拍照的奧秘。

They says the main key is to be female - and to show your hair, but cut off your forehead in your snaps.

他們得出的結(jié)果是，照片中的你首先要是個(gè)女性，——你要秀出你的頭發(fā)，剪掉劉海。

Andrej Karpathy, a PhD student at Stanford working on Deep Learning, decided to use a powerful, 140-million-parameter state-of-the-art Convolutional Neural Network to help work out why some selfies are more popular than other.

安德雷·卡帕西，斯坦福一個(gè)研究計(jì)算機(jī)深度學(xué)習(xí)的博士生，決定使用包含1.4億個(gè)參數(shù)的強(qiáng)大卷積神經(jīng)網(wǎng)絡(luò)來研究為何有的自拍更受歡迎。

'We decided to feed it 2 million selfies from the internet, and train it to classify good selfies from bad ones,' he explained in a blog.

他在博客中這樣解釋：“我們決定使用互聯(lián)網(wǎng)上的兩百萬張照片，教會(huì)系統(tǒng)區(qū)分出好照片。

The neural network, known as ConvNet 'looked' at every one of the 2 million selfies several tens of times.

這個(gè)叫做“ConvNet的神經(jīng)網(wǎng)絡(luò)系統(tǒng)，要“看兩百萬照片中的每一張數(shù)十次。

Each time, it tuned its filters in a way that best allows it to separate good selfies from bad ones.

每一次，它都要調(diào)整過濾器，以最好地實(shí)現(xiàn)好壞照片的區(qū)分。

'We can't very easily inspect exactly what it found (it's all jumbled up in 140 million numbers that together define the filters),' said Karpathy.

卡帕西說，“要檢查系統(tǒng)到底發(fā)現(xiàn)了什么并不容易，(1.4億個(gè)參數(shù)混雜在一起定義了過濾器)。

'However, we can set it loose on selfies that it has never seen before and try to understand what it's doing by looking at which images it likes and which ones it does not. '

“但是我們可以在系統(tǒng)沒審閱過的自拍圖片上放松系統(tǒng)，試圖通過看系統(tǒng)對(duì)圖片的好惡看出些端倪。

'A few patterns stand out for me,' he said.

“慢慢的就發(fā)現(xiàn)了一些規(guī)律。他說。

Women were consistently ranked higher than men - to the extent there was not a single male in the top 100.

女性的自拍總是能評(píng)上高分——以至于前100名連一個(gè)男性也沒有。

The position and pose of the face is quite consistent among the top images.

排名靠前的圖片中，臉部的拍攝位置和姿態(tài)都很一致。

The face always occupies about 1/3 of the image, is slightly tilted, and is positioned in the center and at the top.

圖片的1/3是臉部，略傾斜，位于中央或圖片上部。

If you've ever wondered what makes the perfect selfie, some of the world's most powerful computers have been pondering the same question.

如果你在琢磨怎樣自拍更好看，世界上最強(qiáng)大的電腦也在思考著同樣的問題。

Researchers have trained a neural network designed to think like the human brain to analyse millions of selfies to find what works.

研究者訓(xùn)練設(shè)計(jì)的神經(jīng)網(wǎng)絡(luò)像人類那樣思考，以分析數(shù)百萬張自拍照的奧秘。

They says the main key is to be female - and to show your hair, but cut off your forehead in your snaps.

他們得出的結(jié)果是，照片中的你首先要是個(gè)女性，——你要秀出你的頭發(fā)，剪掉劉海。

Andrej Karpathy, a PhD student at Stanford working on Deep Learning, decided to use a powerful, 140-million-parameter state-of-the-art Convolutional Neural Network to help work out why some selfies are more popular than other.

安德雷·卡帕西，斯坦福一個(gè)研究計(jì)算機(jī)深度學(xué)習(xí)的博士生，決定使用包含1.4億個(gè)參數(shù)的強(qiáng)大卷積神經(jīng)網(wǎng)絡(luò)來研究為何有的自拍更受歡迎。

'We decided to feed it 2 million selfies from the internet, and train it to classify good selfies from bad ones,' he explained in a blog.

他在博客中這樣解釋：“我們決定使用互聯(lián)網(wǎng)上的兩百萬張照片，教會(huì)系統(tǒng)區(qū)分出好照片。

The neural network, known as ConvNet 'looked' at every one of the 2 million selfies several tens of times.

這個(gè)叫做“ConvNet的神經(jīng)網(wǎng)絡(luò)系統(tǒng)，要“看兩百萬照片中的每一張數(shù)十次。

Each time, it tuned its filters in a way that best allows it to separate good selfies from bad ones.

每一次，它都要調(diào)整過濾器，以最好地實(shí)現(xiàn)好壞照片的區(qū)分。

'We can't very easily inspect exactly what it found (it's all jumbled up in 140 million numbers that together define the filters),' said Karpathy.

卡帕西說，“要檢查系統(tǒng)到底發(fā)現(xiàn)了什么并不容易，(1.4億個(gè)參數(shù)混雜在一起定義了過濾器)。

'However, we can set it loose on selfies that it has never seen before and try to understand what it's doing by looking at which images it likes and which ones it does not. '

“但是我們可以在系統(tǒng)沒審閱過的自拍圖片上放松系統(tǒng)，試圖通過看系統(tǒng)對(duì)圖片的好惡看出些端倪。

'A few patterns stand out for me,' he said.

“慢慢的就發(fā)現(xiàn)了一些規(guī)律。他說。

Women were consistently ranked higher than men - to the extent there was not a single male in the top 100.

女性的自拍總是能評(píng)上高分——以至于前100名連一個(gè)男性也沒有。

The position and pose of the face is quite consistent among the top images.

排名靠前的圖片中，臉部的拍攝位置和姿態(tài)都很一致。

The face always occupies about 1/3 of the image, is slightly tilted, and is positioned in the center and at the top.

圖片的1/3是臉部，略傾斜，位于中央或圖片上部。