Search Results for author:
Found 9 papers, 2 papers with code
IMPUS: Image Morphing with Perceptually-Uniform Sampling Using Diffusion Models
We present a diffusion-based image morphing approach with perceptually-uniform sampling (IMPUS) that produces smooth, direct and realistic interpolations given an image pair.
Emergent symbolic language based deep medical image classification
In this work, we demonstrate for the first time, the emer-gence of deep symbolic representations of emergent language in the frame-work of image classification.
ESCELL: Emergent Symbolic Cellular Language
In one form of the game, a sender and a receiver observe a set of cells from 5 different cell phenotypes.
Towards Emergent Language Symbolic Semantic Segmentation and Model Interpretability
A UNet-like architecture is used to generate input to the Sender network which produces a symbolic sentence, and a Receiver network co-generates the segmentation mask based on the sentence.
Symbolic Semantic Segmentation and Interpretation of COVID-19 Lung Infections in Chest CT volumes based on Emergent Languages
We show state of the art results for segmentation of COVID-19 lung infections in CT.
Adversarial Attacks with Time-Scale Representations
Third, we generate new adversarial images by projecting back the original coefficients from the low scale and the perturbed coefficients from the high scale sub-space.
Adversarial Purification with the Manifold Hypothesis
In this work, we formulate a novel framework for adversarial robustness using the manifold hypothesis.
Understanding the Unforeseen via the Intentional Stance
Our approach uses analogy with past experiences to construct hypothetical rationales that explain the behavior of an observed agent.
Probabilistic and Semantic Descriptions of Image Manifolds and Their Applications
This paper begins with a description of methods for estimating image probability density functions that reflects the observation that such data is usually constrained to lie in restricted regions of the high-dimensional image space-not every pattern of pixels is an image.
