Instruct: Given a paper title, retrieve paper titles that are cited by the given paper
Query: COFGA: Classification Of Fine-Grained Features In Aerial Images
Object Recognition in Aerial Images Using Convolutional Neural Networks
detection and modeling of buildings from multiple aerial images .
Semantic Segmentation of Aerial Images With Shuffling Convolutional Neural Networks
Vehicle Detection in Aerial Images Based on Region Convolutional Neural Networks and Hard Negative Example Mining
Learning to detect roads in high-resolution aerial images
Hourglass-ShapeNetwork Based Semantic Segmentation for High Resolution Aerial Imagery
Towards Real-Time People Recognition on Aerial Imagery Using Convolutional Neural Networks
Unsupervised Deep Feature Extraction for Remote Sensing Image Classification
On image classification: city images vs. landscapes
Deep contextual description of superpixels for aerial urban scenes classification
Analysis of food images: Features and classification
FALCON: Feature Driven Selective Classification for Energy-Efficient Image Recognition
Fine-Grained Crowdsourcing for Fine-Grained Recognition
Image Classification Based on the Combination of Text Features and Visual Features
Deep feature representations for high-resolution remote-sensing imagery retrieval
Weakly Supervised Fine-Grained Categorization With Part-Based Image Representation
Fast Fine-grained Image Classification via Weakly Supervised Discriminative Localization
Off-the-Shelf CNN Features for Fine-Grained Classification of Vessels in a Maritime Environment
Learning to Label Aerial Images from Noisy Data
Integrated feature selection and higher-order spatial feature extraction for object categorization
IoT based monitoring of container vehicle for secure and reliable delivery of goods
Critical Infrastructure Protection: having SIEM technology cope with network heterogeneity
Bacterial Multidrug Efflux Pumps: Much More Than Antibiotic Resistance Determinants
SnuCL: an OpenCL framework for heterogeneous CPU/GPU clusters
Learning Methods for Generic Object Recognition with Invariance to Pose and Lighting