1 citations · 2 across the 7 of their papers we have counts for
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Probabilistic Embeddings for Frozen Vision-Language Models: Uncertainty Quantification with Gaussian Process Latent Variable Models
Aishwarya Venkataramanan, Paul Bodesheim, Joachim Denzler
Vision-Language Models (VLMs) learn joint representations by mapping images and text into a shared latent space. However, recent research highlights that deterministic embeddings f…
Integrating Visual and Semantic Similarity Using Hierarchies for Image Retrieval
Aishwarya Venkataramanan, Martin Laviale, Cédric Pradalier
Most of the research in content-based image retrieval (CBIR) focus on developing robust feature representations that can effectively retrieve instances from a database of images th…
Gaussian Latent Representations for Uncertainty Estimation using Mahalanobis Distance in Deep Classifiers
Aishwarya Venkataramanan, Assia Benbihi, Martin Laviale +1
Recent works show that the data distribution in a network's latent space is useful for estimating classification uncertainty and detecting Out-of-distribution (OOD) samples. To obt…
Tackling Inter-Class Similarity and Intra-Class Variance for Microscopic Image-based Classification
Aishwarya Venkataramanan, Martin Laviale, Cécile Figus +2
Automatic classification of aquatic microorganisms is based on the morphological features extracted from individual images. The current works on their classification do not conside…