Instruct: Given the title of a scientific paper, retrieve paper titles that are cited by the given paper.
Query: People counting and pedestrian flow statistics based on convolutional neural network and recurrent neural network
Switching Convolutional Neural Network for Crowd Counting
Fused Deep Neural Networks for Efficient Pedestrian Detection
A recurrent neural network that learns to count
Skip-connection convolutional neural network for still image crowd counting
Predicting Short-Term Traffic Flow by Long Short-Term Memory Recurrent Neural Network
Single-Image Crowd Counting via Multi-Column Convolutional Neural Network
Pedestrian Color Naming via Convolutional Neural Network
GAIT RECOGNITION BASED ON CONVOLUTIONAL NEURAL NETWORKS
Count-ception: Counting by Fully Convolutional Redundant Counting
Pedestrian Detection and Tracking for Counting Applications in Crowded Situations
Mixture of Counting CNNs: Adaptive Integration of CNNs Specialized to Specific Appearance for Crowd Counting
Fusing LIDAR and images for pedestrian detection using convolutional neural networks
Counting in Dense Crowds using Deep Features
Multispectral Pedestrian Detection using Deep Fusion Convolutional Neural Networks
A WiFi-based method to count and locate pedestrians in urban traffic scenarios
A Novel Method for Tracking and Counting Pedestrians in Real-Time Using a Single Camera
Depth driven people counting using deep region proposal network
Leaf Counting with Deep Convolutional and Deconvolutional Networks
Pedestrian recognition with a learned metric
People Counting in High Density Crowds from Still Images
Non-Autoregressive Neural Machine Translation
GUIDELINES ON THE PREVENTION, DIAGNOSIS, AND TREATMENT OF INFECTIVE ENDOCARDITIS (NEW VERSION 2009)
Propranolol for Orbital Hemangioma
Face Recognition Using Kernel Ridge Regression
Analysis of Metastability Errors in Conventional, LSB-First, and Asynchronous SAR ADCs