Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper
Query: Cascaded one-vs-rest detection network for fine-grained recognition without part annotations
Part-based R-CNNs for Fine-grained Category Detection
Fully Convolutional Attention Networks for Fine-Grained Recognition
Weakly Supervised Learning of Part Selection Model with Spatial Constraints for Fine-Grained Image Classification
Fine-Grained Categorization via CNN-Based Automatic Extraction and Integration of Object-Level and Part-Level Features
Empirical Analysis of Detection Cascades of Boosted Classifiers for Rapid Object Detection
Fused one-vs-all mid-level features for fine-grained visual categorization
Text Detection by Faster R-CNN with Multiple Region Proposal Networks
Object Detection Based on Multi-Layer Convolution Feature Fusion and Online Hard Example Mining
Fused One-vs-All Features With Semantic Alignments for Fine-Grained Visual Categorization
A Multi-part Convolutional Attention Network for Fine-Grained Image Recognition
Robust object detection via soft cascade
Multiple Instance Detection Network with Online Instance Classifier Refinement
DetNet: A Backbone network for Object Detection
Con-Text: Text Detection for Fine-Grained Object Classification
Object Detection Using the Statistics of Parts
Deformable Part-based Fully Convolutional Network for Object Detection
Deep Neural Networks for Object Detection
Object Detection Networks on Convolutional Feature Maps
Recursive neural networks for object detection
AOGNets: Deep AND-OR Grammar Networks for Visual Recognition.
A pilot randomised controlled trial to evaluate the feasibility and acceptability of the Baby Triple P Positive Parenting Programme in mothers with postnatal depression
Effect of virgin coconut meal (VCM) on the rheological, micro-structure and baking properties of cake and batter
Support-vector networks
Transformation Based Ensembles for Time Series Classification
One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning