activity
20172026
most citedDeep Unsupervised Contrastive Hashing for Large-Scale Cross-Modal Text-Image Retrieval in Remote Sensing

21 citations · 50 across the 11 of their papers we have counts for

collaborators

16 papers

cs.IR2026

VCG: A Multimodal Retrieval Framework for E-Commerce Video Feeds under Extreme Cold-Start Conditions

Katya Mirylenka, Egor Malykh, Mahdyar Ravanbakhsh +10

The digital commerce landscape is shifting from static, search-driven catalogs to dynamic, immersive video feeds. This transition introduces an ``extreme cold-start'' problem: unli…

cs.IR2025

Agentic Personalized Fashion Recommendation in the Age of Generative AI: Challenges, Opportunities, and Evaluation

Yashar Deldjoo, Nima Rafiee, Mahdyar Ravanbakhsh

Fashion recommender systems (FaRS) face distinct challenges due to rapid trend shifts, nuanced user preferences, intricate item-item compatibility, and the complex interplay among…

cs.CV20224 cited

Advanced Deep Learning Architectures for Accurate Detection of Subsurface Tile Drainage Pipes from Remote Sensing Images

Tom-Lukas Breitkopf, Leonard W. Hackel, Mahdyar Ravanbakhsh +4

Subsurface tile drainage pipes provide agronomic, economic and environmental benefits. By lowering the water table of wet soils, they improve the aeration of plant roots and ultima…

cs.CV20222 cited

Multi-Modal Fusion Transformer for Visual Question Answering in Remote Sensing

Tim Siebert, Kai Norman Clasen, Mahdyar Ravanbakhsh +1

With the new generation of satellite technologies, the archives of remote sensing (RS) images are growing very fast. To make the intrinsic information of each RS image easily acces…

cs.CV20222 cited

Unsupervised Contrastive Hashing for Cross-Modal Retrieval in Remote Sensing

Georgii Mikriukov, Mahdyar Ravanbakhsh, Begüm Demir

The development of cross-modal retrieval systems that can search and retrieve semantically relevant data across different modalities based on a query in any modality has attracted…

cs.CV2022

An Unsupervised Cross-Modal Hashing Method Robust to Noisy Training Image-Text Correspondences in Remote Sensing

Georgii Mikriukov, Mahdyar Ravanbakhsh, Begüm Demir

The development of accurate and scalable cross-modal image-text retrieval methods, where queries from one modality (e.g., text) can be matched to archive entries from another (e.g.…