Deep Learning of Principal Component for Car Model Recognition
نویسندگان
چکیده
Vehicle detection and analysis is widely used in various applications, such as automatic toll collection, driver assistance systems. Among these applications, car make and model recognition is a challenging task due to the close appearance between car models. In this paper, we proposed a novel algorithm based on deep learning of principal component (DLPC) to recognize the car make and model. Considering the 3D complexity of a car, we extract the frontal view of a car to recognize the make and model. After that, we transform the frontal view of a car to its feature mapping using principal component analysis (PCA). Finally, we use deep learning with three layers of restricted Boltzmann machines (RBMs) to recognize the car make and model. Experiment results show that our proposed framework achieves favorable recognition accuracy.
منابع مشابه
Sparse Structured Principal Component Analysis and Model Learning for Classification and Quality Detection of Rice Grains
In scientific and commercial fields associated with modern agriculture, the categorization of different rice types and determination of its quality is very important. Various image processing algorithms are applied in recent years to detect different agricultural products. The problem of rice classification and quality detection in this paper is presented based on model learning concepts includ...
متن کاملObject Recognition based on Local Steering Kernel and SVM
The proposed method is to recognize objects based on application of Local Steering Kernels (LSK) as Descriptors to the image patches. In order to represent the local properties of the images, patch is to be extracted where the variations occur in an image. To find the interest point, Wavelet based Salient Point detector is used. Local Steering Kernel is then applied to the resultant pixels, in ...
متن کاملA Hybrid Algorithm based on Deep Learning and Restricted Boltzmann Machine for Car Semantic Segmentation from Unmanned Aerial Vehicles (UAVs)-based Thermal Infrared Images
Nowadays, ground vehicle monitoring (GVM) is one of the areas of application in the intelligent traffic control system using image processing methods. In this context, the use of unmanned aerial vehicles based on thermal infrared (UAV-TIR) images is one of the optimal options for GVM due to the suitable spatial resolution, cost-effective and low volume of images. The methods that have been prop...
متن کاملمدل ترکیبی تحلیل مؤلفه اصلی احتمالاتی بانظارت در چارچوب کاهش بعد بدون اتلاف برای شناسایی چهره
In this paper, we first proposed the supervised version of probabilistic principal component analysis mixture model. Then, we consider a learning predictive model with projection penalties, as an approach for dimensionality reduction without loss of information for face recognition. In the proposed method, first a local linear underlying manifold of data samples is obtained using the supervised...
متن کاملPrediction of mineral deposit model and identification of mineralization trend in depth using frequency domain of surface geochemical data in Dalli Cu-Au porphyry deposit
In this research work, the frequency domain (FD) of surface geochemical data was analyzed to decompose the complex geochemical patterns related to different depths of the mineral deposit. In order to predict the variation in mineralization in the depth and identify the deep geochemical anomalies and blind mineralization using the surface geochemical data for the Dalli Cu-Au porphyry deposit, a ...
متن کامل