Instruct: Given a paper title, retrieve paper titles that are cited by the given paper
Query: A novel feature descriptor for image retrieval by combining modified color histogram and diagonally symmetric co-occurrence texture pattern
Histogram refinement for texture descriptor based image retrieval
Regional Attention Based Deep Feature for Image Retrieval
Effects of different Gabor filters parameters on image retrieval by texture
Local jet pattern: a robust descriptor for texture classification
A new biologically inspired color image descriptor
Color texture classification by integrative Co-occurrence matrices
Colour appearance descriptors for image browsing and retrieval
evaluating the potential of texture and color descriptors for remote sensing image retrieval and classification .
A Discriminative Framework for Texture and Object Recognition Using Local Image Features
Local Wavelet Pattern: A New Feature Descriptor for Image Retrieval in Medical CT Databases
Design and Implementation of an Efficient Image Retrieval System using Spatial Feature Reduction
BOLD - Binary online learned descriptor for efficient image matching
Development of an Improved Feature based Algorithm for Image Matching
Fundamental of Content Based Image Retrieval
An improvement to the SIFT descriptor for image representation and matching
Comparison of texture features based on Gabor filters
A comparative experimental study of image feature detectors and descriptors
Novel Color LBP Descriptors for Scene and Image Texture Classification
Two-stage pooling of deep convolutional features for image retrieval
Towards Good Practices for Image Retrieval Based on CNN Features
TAC-GAN - Text Conditioned Auxiliary Classifier Generative Adversarial Network
Detection and quantification of Bacillus cereus group in milk by droplet digital PCR.
Visual categorization with bags of keypoints
Modelling respiration rate of fresh fruits and vegetables for modified atmosphere packages: a review
Technology acceptance model (TAM) and social media usage: an empirical study on Facebook