Search Results for author:
Found 11 papers, 2 papers with code
DEff-GAN: Diverse Attribute Transfer for Few-Shot Image Synthesis
While single image methods can synthesize image samples with diversity, they do not model multiple images or capture the inherent relationship possible between two images.
FPCD: An Open Aerial VHR Dataset for Farm Pond Change Detection
In this paper, we introduce a publicly available object detection and instance segmentation (OD/IS) dataset for localizing farm ponds from aerial imagery.
Deriving Surface Resistivity from Polarimetric SAR Data Using Dual-Input UNet
DI-UNet uses a deep learning architecture to predict the resistivity using full polarimetric SAR data by promising a quick survey addition to the traditional method.
The MIS Check-Dam Dataset for Object Detection and Instance Segmentation Tasks
Deep learning has led to many recent advances in object detection and instance segmentation, among other computer vision tasks.
Learning Unsupervised Cross-domain Image-to-Image Translation Using a Shared Discriminator
We assess the qualitative and quantitative results on image transfiguration, a cross-domain translation task, in a setting where the target domain shares similar semantics to the source domain.
Ranked #1 on
Image-to-Image Translation
on Zebra and Horses
Symbolic powers of certain cover ideals of graphs
In this paper, we compute the regularity and Hilbert series of symbolic powers of the cover ideal of a graph $G$ when $G$ is either a crown graph or a complete multipartite graph.
Commutative Algebra 13D02, 13F20
Basis Pursuit Denoise with Nonsmooth Constraints
These formulations are widely used, particularly for matrix completion and sparsity promotion in data interpolation and denoising.
Simultaneous shot inversion for nonuniform geometries using fast data interpolation
Stochastic optimization is key to efficient inversion in PDE-constrained optimization.
Beating level-set methods for 3D seismic data interpolation: a primal-dual alternating approach
Acquisition cost is a crucial bottleneck for seismic workflows, and low-rank formulations for data interpolation allow practitioners to `fill in' data volumes from critically subsampled data acquired in the field.
K-Algorithm A Modified Technique for Noise Removal in Handwritten Documents
In the present paper, a modified technique for noise removal named as K-Algorithm has been proposed, which has two stages as filtering and binarization.
Fast methods for denoising matrix completion formulations, with applications to robust seismic data interpolation
In this paper, we consider matrix completion formulations designed to hit a target data-fitting error level provided by the user, and propose an algorithm called LR-BPDN that is able to exploit factorized formulations to solve the corresponding optimization problem.
