We redesigned the GUI, and the program was optimized.
Have a look:
1、4 steps for pic recognition:
2、You can select bounding-box by yourself:
This is a Matlab lesson design for vehicle detection and recognition. Using cifar-10Net to training a RCNN, and finetune AlexNet to classify. Thanks to Cars Dataset : http://ai.stanford.edu/~jkrause/cars/car_dataset.html
Matlab R2016b
cars_meta.mat : http://pan.baidu.com/s/1mi6nvr6
cifar10NetRCNN.mat : (for Car position detection) http://pan.baidu.com/s/1geLa1V1
AlexNet_New.mat : (for Car type classify) http://pan.baidu.com/s/1bEzcYE
You can use it to finish your task for single picture or video. Make sure your picture or video frame has 3 channels (colorful)
3D Object Representations for Fine-Grained CategorizationJonathan Krause, Michael Stark, Jia Deng, Li Fei-Fei4th IEEE Workshop on 3D Representation and Recognition, at ICCV 2013 (3dRR-13). Sydney, Australia. Dec. 8, 2013.
DataSet : http://ai.stanford.edu/~jkrause/cars/car_dataset.html
Actually, The running speed of the program is a bit of slow... Hope you can try Faster-Rcnn or yolo (you only look once).
介绍: 本文全面回顾了车辆检测方法及其在智能车辆系统中的应用,分析了车辆检测的发展,重点介绍了传感器类型和算法分类。首先,本文总结了300多项研究成果,包括各种车辆检测传感器(机器视觉、毫米波雷达、激光雷达和多传感器融合),并详细比较了经典算法和最新算法的性能。然后,根据不同传感器和算法的性能和适用性,分析了它们在车辆检测中的应用场景。此外,我们还系统地总结了恶劣天气下的车辆检测方法。最后,根据智