面部识别毕业论文

面部识别毕业论文

可以。
毕业论文是可以用别人训练出来的，但是自己也要有创新，不能全部使用，不然是不会过的。
毕业论文（graduation study）是专科及以上学历教育为对本专业学生集中进行科学研究训练而要求学生在毕业前撰写的论文。毕业论文一般安排在修业的最后一学年（学期）进行，论文题目由教师指定或由学生提出，学生选定课题后进行研究，撰写并提交论文，目的在于培养学生的科学研究能力，加强综合运用所学知识、理论和技能解决实际问题的训练，从总体上考查学生大学阶段学习所达到的学业水平。

毕业答辩时老师会问什么问题?我做的是人脸识别算法方面的论文

＝＝你是本科还是硕士啊
论文的话应该主要是算法的研究和改进吧……
问题比如：你采用了哪种人脸识别算法
你对这种算法的改进在哪里(你不只要说明改进在哪里
可能还需要做一些实验收集下数据来对比
说明算法在改进后对性能有了提升)
新算法比其他算法好在哪里(还是通过实验收集数据对比一下)
分析下算法的复杂度(时间复杂度和空间复杂度可能都会要求
毕竟图像分析很占空间)
然后是怎样进行优化的
实验采用的样本是哪些(我们当时用的UC
Irvine
Machine
Learning
Repository
下面会有CMU
Face
Images
大家一般都用这个库来作为样本)
怎样对实验结果进行量化比较的(标准是什么)
如果是模式识别的话
还可能关心怎样选的特征值和特征空间(计算量大的话是怎样减少计算量的)
训练样本采用的什么算法
实验的识别率是多少
算法的性能是不是稳定……
＝＝我想到的都是本科的问题
如果是研究生的话可能还会问的更难

哪个好人帮我翻译一下毕业论文的摘要，谢谢啦

The interaction between man and computer activities of daily life is increasingly becoming an important part of, especially in recent years, with the rapid development of computer technology to study the habits of the new line interpersonal communication interpersonal interaction techniques become very active at the same time also made encouraging progress, these studies include face recognition, facial expression recognition, gesture recognition, etc..
Gesture is a natural, intuitive, easy to learn human-computer interaction means. Manual directly as computer input devices, human-computer communication between the middle of the media will no longer need, the user can simply define an appropriate gesture to the surrounding machine control, therefore, gesture recognition is a human and robot interaction an important tool, but also human-computer interaction, virtual reality, an important component. However, the gesture itself, the diversity, ambiguity and the staff is a complex deformation body and the visual is inherently uncertain, coupled with staff is a complex deformation of their body and visual discomfort qualitative, making vision-based gesture recognition is a very challenging interdisciplinary research topic.
This article focuses on the general context of gesture segmentation and the use of BP neural network to recognize the gesture. Gestures are defined in advance, and the input to the neural network was trained, and then collected through the use of color image opencv extract-based skin color, the color images from complex background, hand in the image, further processing and enter the neural network identification.