Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper.
Query: Joint Optic Disc and Cup Segmentation Based on Multi-label Deep Network and Polar Transformation
Superpixel Classification Based Optic Disc and Optic Cup Segmentation for Glaucoma Screening
Retinal fluid segmentation in OCT images using adversarial loss based convolutional neural networks
Optic disc localization in retinal images using histogram matching
Deep Stereo Fusion: Combining Multiple Disparity Hypotheses with Deep-Learning
DeepCrop : Directed Object Segmentation with Deep Learning
Automated localisation of retinal optic disk using Hough transform
DispSegNet: Leveraging Semantics for End-to-End Learning of Disparity Estimation from Stereo Imagery
ReLayNet: Retinal Layer and Fluid Segmentation of Macular Optical Coherence Tomography using Fully Convolutional Network
Automatic optic disc detection in digital fundus images using image processing
Depth-based segmentation — A review
Automated detection of optic disc and blood vessel in retinal image using morphological, edge detection and feature extraction technique
A Labeling-Free Approach to Supervising Deep Neural Networks for Retinal Blood Vessel Segmentation
Ordinal Image Segmentation using Deep Neural Networks
A new method for image segmentation
Dual Attention Network for Scene Segmentation
Simultaneous Detection and Segmentation
Superpixel Segmentation: An Evaluation
Segmentation with low depth of field images
Drishti-GS: Retinal image dataset for optic nerve head(ONH) segmentation
Retinal Vessel Segmentation Using Deep Neural Networks
Grating lobe suppression of narrow-wall slotted waveguide array antenna using thin narrow-wall waveguides in millimeter-wave band
Herbal Cosmetics for Skin and Hair care
A Randomized, Double-Blind, Multicenter Comparison of the Efficacy and Tolerability of Restylane Versus Zyplast for the Correction of Nasolabial Folds
Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations
Compromising Emanations: Eavesdropping Risks of Computer Displays