Publication

Dynamic overview techniques for image retrieval

Related publications (58)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

From scattered sources to comprehensive technology landscape : A recommendation-based retrieval approach

Karl Aberer, Chi Thang Duong

Mapping the technology landscape is crucial for market actors to take informed investment decisions. However, given the large amount of data on the Web and its subsequent information overload, manually retrieving information is a seemingly ineffective and ...

ELSEVIER2023

Knowledge-Aware Cross-Modal Text-Image Retrieval for Remote Sensing Images

Devis Tuia, Christel Marie Tartini-Chappuis, Li Mi, Siran Li

Image-based retrieval in large Earth observation archives is difficult, because one needs to navigate across thousands of candidate matches only with the proposition image as a guide. By using text as a query language, the retrieval system gains in usabili ...

2022

Graph Embedding for Retrieval

Chi Thang Duong

Information retrieval (IR) systems such as search engines are important for people to find what they need among the tremendous amount of data available in their organization or on the Internet. These IR systems enable users to search in a large data collec ...

EPFL2022

QAIR: Practical Query-efficient Black-Box Attacks for Image Retrieval

Shaokai Ye, Yuan He, Hang Su, Jinfeng Li

We study the query-based attack against image retrieval to evaluate its robustness against adversarial examples under the black-box setting, where the adversary only has query access to the top-1 ranked unlabeled images from the database. Compared with que ...

IEEE COMPUTER SOC2021

Learning Representations of Source Code from Structure and Context

Large codebases are routinely indexed by standard Information Retrieval systems, starting from the assumption that code written by humans shows similar statistical properties to written text [Hindle et al., 2012]. While those IR systems are still relativel ...

2019

Adaptive relevance feedback for large-scale image retrieval

François Fleuret, Nicolae Suditu

Content-based image retrieval aims at substituting traditional indexing based on manual annotation by using automatically-extracted visual indexing features. Novel techniques are needed however to efficiently deal with the semantic gap (i.e. the partial ma ...

2016

MEM0R1ES: Memory-based Information Systems

Michele Catasta

The advent of the Web reshaped the way in which humans memorize information, arguably unlike any other technological advance of the last decades. Rather than remembering the information itself, people are primed to find the needed information through Web s ...

EPFL2015

Enforcing Topic Diversity in a Document Recommender for Conversations

Andrei Popescu-Belis, Maryam Habibi

This paper addresses the problem of building concise, diverse and relevant lists of documents, which can be recommended to the participants of a conversation to fulfill their information needs without distracting them. These lists are retrieved periodicall ...

2014

Adaptive Relevance Feedback for Large-scale Image Retrieval

Nicolae Suditu

Our research addresses the need for an efficient, effective, and interactive access to large-scale image collections. Image retrieval needs are evolving beyond the capabilities of the traditional indexing based on manual annotation, and the most desirable ...

EPFL2013

Iterative EEG-based Natural Image Search under RSVP

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Marija Uscumlic

This work extends previous studies on using EEG decoding for automatic image retrieval. We propose an iterative way to integrate the information obtained from the EEG decoding and image processing methods. In the light of real-world BCI applications, we de ...

Graz University of Technology Publishing House2013