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Found 10 papers, 4 papers with code
HyperFast: Instant Classification for Tabular Data
Training deep learning models and performing hyperparameter tuning can be computationally demanding and time-consuming.
Adversarial Learning for Feature Shift Detection and Correction
Data shift is a phenomenon present in many real-world applications, and while there are multiple methods attempting to detect shifts, the task of localizing and correcting the features originating such shifts has not been studied in depth.
Manipulation Detection in Satellite Images Using Vision Transformer
A growing number of commercial satellite companies provide easily accessible satellite imagery.
Saliency-Aware Class-Agnostic Food Image Segmentation
Our method uses a pair of eating scene images, one before start eating and one after eating is completed.
Generative Autoregressive Ensembles for Satellite Imagery Manipulation Detection
Satellite imagery is becoming increasingly accessible due to the growing number of orbiting commercial satellites.
Addressing Ancestry Disparities in Genomic Medicine: A Geographic-aware Algorithm
With declining sequencing costs a promising and affordable tool is emerging in cancer diagnostics: genomics.
Genomics Populations and Evolution
Deepfakes Detection with Automatic Face Weighting
Altered and manipulated multimedia is increasingly present and widely distributed via social media platforms.
LAI-Net: Local-Ancestry Inference with Neural Networks
Local-ancestry inference (LAI), also referred to as ancestry deconvolution, provides high-resolution ancestry estimation along the human genome.
Multi-View Matching Network for 6D Pose Estimation
Applications that interact with the real world such as augmented reality or robot manipulation require a good understanding of the location and pose of the surrounding objects.
Class-Conditional VAE-GAN for Local-Ancestry Simulation
Techniques to generate training samples that resemble real haploid sequences from ancestries of interest can be useful tools in such scenarios, since a generalized model can often be shared, but the unique human sample sequences cannot.
