CMU的noisex92数据集的完全版,最低积分提供给大家共享。
2021-11-22 11:18:20 73.61MB noise data
1
csapp shell lab 满分原创(北大&cmu;) 仅供参考,请勿抄袭
2021-11-22 03:56:31 7KB csapp shell lab 满分原创
1
这是卡内基梅隆大学的公开人脸测试集。测试集共分四个文件夹,分别为测试集A、B、C和旋转测试集。由于大小限制,因此将四个文件夹分开上传 The image dataset is used by the CMU Face Detection Project and is provided for evaluating algorithms for detecting frontal views of human faces. This particular test set was originally assembled as part of work in Neural Network Based Face Detection. It combines images collected at CMU and MIT. Please give appropriate acknowledgements when you use these test sets. In the lists of files below, you will find references to Test Sets A, B, C and the Rotated Test Set. Test Set B was provided by Kah-Kay Sung and Tomaso Poggio at the AI/CBCL Lab at MIT, and Test Sets A,C and the rotatated test set were collected here at CMU (by Henry A. Rowley, Shumeet Baluja, and Takeo Kanade). In [Schneiderman and Kanade, 2000] and [Schneiderman and Kanade, 1998] we refer to the combination of test sets A, B, and C as the "combined test sets of Sung and Poggio and Rowley, Baluja, and Kanade." In [Rowley, Baluja, and Kanade, 1998] we refer to the combination of sets A, B, C as "test set one" and in [Rowley, Baluja, and Kanade, 1997] we refer to it as the "upright set" as distinguished from the "rotated set."
2021-11-09 17:03:44 1.7MB cmu mit 人脸检测 人脸
1
这是卡内基梅隆大学的公开人脸测试集。测试集共分四个文件夹,分别为测试集A、B、C和旋转测试集。由于大小限制,因此将四个文件夹分开上传 The image dataset is used by the CMU Face Detection Project and is provided for evaluating algorithms for detecting frontal views of human faces. This particular test set was originally assembled as part of work in Neural Network Based Face Detection. It combines images collected at CMU and MIT. Please give appropriate acknowledgements when you use these test sets. In the lists of files below, you will find references to Test Sets A, B, C and the Rotated Test Set. Test Set B was provided by Kah-Kay Sung and Tomaso Poggio at the AI/CBCL Lab at MIT, and Test Sets A,C and the rotatated test set were collected here at CMU (by Henry A. Rowley, Shumeet Baluja, and Takeo Kanade). In [Schneiderman and Kanade, 2000] and [Schneiderman and Kanade, 1998] we refer to the combination of test sets A, B, and C as the "combined test sets of Sung and Poggio and Rowley, Baluja, and Kanade." In [Rowley, Baluja, and Kanade, 1998] we refer to the combination of sets A, B, C as "test set one" and in [Rowley, Baluja, and Kanade, 1997] we refer to it as the "upright set" as distinguished from the "rotated set."
2021-11-09 16:54:14 5.69MB cmu mit 人脸检测 人脸
1
matlab的slam代码16-833 机器人 SLAM (16-833) @CMU 的作业 如果你目前正在学习 16-833 课程,我鼓励你自己尝试作业,最好不要使用这里的代码片段 - 因为这违反了学院的学术诚信政策。 如果您在这里学习不同的概念,请继续并参考任何片段。 作业 1 - 粒子过滤器(实习,Python) 作业 2 - 扩展卡尔曼滤波器(实践,MATLAB) 作业 3 - 线性和非线性 SLAM 求解器(实习,MATLAB) 作业 4 - ICP 和基于点的融合(实习,MATLAB)
2021-11-08 08:01:20 30.2MB 系统开源
1
CMU-CloudFS
2021-10-31 13:45:34 1.24MB C
1
CMU ICS课程教材, 国内更常称为ICS(Introduction to Computer System), 计算机入门教材。总共十二章节。
2021-10-31 06:38:40 6.75MB CSAPP ICS CMU
1
采用seg-list结构,易于理解,适合和我一样的弱渣使用,好好调参,可以得到优秀分,我觉得挺不错,亲测好用,大家快来下载吧
2021-10-28 06:49:47 13KB csapp
1
Malloc实验室 CMU 的 Malloc Lab 仅包含 mm.c(98/100 性能),并附有详细注释
2021-10-21 22:09:47 4KB C
1
CMU(美国卡耐基梅隆大学,Carnegie Mellon University,人工智能/深度学习领域最著名的大学之一)的深度学习课程的讲义,配合案例讲解原理,十分清晰详细地介绍了深度学习典型方法的基本原理,包括感知器、BP、卷积网络、循环网络以及相关优化方法等。
2021-10-21 15:19:53 39.44MB 人工智能 深度学习 神经网络
1