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Image-Analysis

所属分类:模式识别(视觉/语音等)
开发工具:matlab
文件大小:31867KB
下载次数:0
上传日期:2017-09-06 20:12:58
上 传 者sh-1993
说明:  图像分析,用于图像分析和物体识别的C++Malab编程
(Image-Analysis,C++ Malab Programming for Image analysis and object recognition)

文件列表:
Ex2 - Image filtering and interest point operators Gradient of Gaussian filtering and F_rstner interest points (0, 2017-09-07)
Ex2 - Image filtering and interest point operators Gradient of Gaussian filtering and F_rstner interest points\02_Assignment2_04052017.pdf (3713670, 2017-09-07)
Ex2 - Image filtering and interest point operators Gradient of Gaussian filtering and F_rstner interest points\Assignment2_04052017.pdf (408123, 2017-09-07)
Ex2 - Image filtering and interest point operators Gradient of Gaussian filtering and F_rstner interest points\Ex1 Images.jpg (11108, 2017-09-07)
Ex2 - Image filtering and interest point operators Gradient of Gaussian filtering and F_rstner interest points\Ex2 Images.jpg (11680, 2017-09-07)
Ex2 - Image filtering and interest point operators Gradient of Gaussian filtering and F_rstner interest points\GoG.m (1763, 2017-09-07)
Ex2 - Image filtering and interest point operators Gradient of Gaussian filtering and F_rstner interest points\Thumbs.db (14336, 2017-09-07)
Ex2 - Image filtering and interest point operators Gradient of Gaussian filtering and F_rstner interest points\forstnerOperation.m (1966, 2017-09-07)
Ex2 - Image filtering and interest point operators Gradient of Gaussian filtering and F_rstner interest points\input_exercise2.png (14143, 2017-09-07)
Ex3 - Hough line detection (0, 2017-09-07)
Ex3 - Hough line detection\03_Assignment3_18052017.pdf (2151069, 2017-09-07)
Ex3 - Hough line detection\GoG.m (1767, 2017-09-07)
Ex3 - Hough line detection\Test Images (0, 2017-09-07)
Ex3 - Hough line detection\Test Images\BW at 1.fig (42066, 2017-09-07)
Ex3 - Hough line detection\Test Images\G at 0.5 .fig (1650077, 2017-09-07)
Ex3 - Hough line detection\Test Images\G at 1 .fig (2002774, 2017-09-07)
Ex3 - Hough line detection\assignment3_18052017.pdf (439057, 2017-09-07)
... ...

# Fast-RCNN demo This folder contains an example implementation of Fast-RCNN [1] in MatConvNet. The example trains and test on the PASCAL VOC 2007 data. There are three entry-point scripts: * `fast_rcnn_demo.m`: runs the original Caffe model imported in MatConvNet. * `fast_rcnn_train.m`: trains a new model from scratch, using pre-computed proposals. * `fast_rcnn_evaluate.m`: evaluates the trained model. Note that the code does not ship with a proposal generation method, so proposals must be precomputed (using e.g. edge boxes or selective search windows). The `fast_rcnn_demo.m` code should run out of the box, downloading the model as needed. To test the training code using the first GPU on your system, use something like: run matlab/vl_setupnn addpath examples/fast_rcnn fast_rcnn_train('train',struct('gpus',1)) ; fast_rcnn_evaluate('gpu',1) ; ## References 1. *Fast R-CNN*, R. Girshick, International Conference on Computer Vision (ICCV), 2015.

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