Instruct: Given a paper title, retrieve paper titles that are cited by the given paper.
Query: A systematic evaluation of recent deep learning architectures for fine-grained vehicle classification
A large-scale car dataset for fine-grained categorization and verification
Online vehicle detection using Haar-like, LBP and HOG feature based image classifiers with stereo vision preselection
A Vehicle Recognition Algorithm Based on Deep Transfer Learning with a Multiple Feature Subspace Distribution
Multi-shape Descriptor Vehicle Classification for Urban Traffic
Vehicle logo detection using convolutional neural network and pyramid of histogram of oriented gradients
Vehicle detection from high-resolution aerial images using spatial pyramid pooling-based deep convolutional neural networks
DepthCN: Vehicle detection using 3D-LIDAR and ConvNet
Fine-Grained Car Detection for Visual Census Estimation
Deep Learning in the Automotive Industry: Applications and Tools
Vehicle Detection in Satellite Images by Hybrid Deep Convolutional Neural Networks
Fast Vehicle Detection with Lateral Convolutional Neural Network
Deep Learning Lane Detection for Autonomous Vehicle Localization
Diversified Visual Attention Networks for Fine-Grained Object Classification
Reach on Sobel Operator for Vehicle Recognition
On-road vehicle detection: a review
Vehicle color recognition using deep learning for hazy images
Hyper-class augmented and regularized deep learning for fine-grained image classification
Building Robust Deep Neural Networks for Road Sign Detection
VRSDNet: vehicle re-identification with a shortly and densely connected convolutional neural network
BoxCars: Improving Fine-Grained Recognition of Vehicles using 3D Bounding Boxes in Traffic Surveillance
Binary Artificial Bee Colony optimization using bitwise operation
A (Very) Brief History of Artificial Intelligence
Hemicorporectomy as a life-saving strategy for severe pelvic ring crush injury: a case report
Developing and delivering hands-on information assurance exercises: experiences with the cyber defense lab at UMBC
Caffe: Convolutional Architecture for Fast Feature Embedding