Application of Information Retrieval Techniques to Single Writer Documents
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.
This work shows experiments on the retrieval of handwritten documents. The performance of the same state-of-the-art Information Retrieval system is compared when dealing with manual (no errors) and automatic (Word Error Rate around 50%) transcriptions of t ...
This work shows experiments on the retrieval of handwritten documents. The performance of the same state-of-the-art Information Retrieval system is compared when dealing with manual (no errors) and automatic (Word Error Rate around 50%) transcriptions of t ...
Text embedded in images and videos represents a rich source of information for content-based indexing and retrieval applications. In this paper, we present a new method for localizing and recognizing text in complex images and videos. Text localization is ...
Text characters embedded in images and video sequences represents a rich source of information for content-based indexing and retrieval applications. However, these text characters are difficult to be detected and recognized due to their various sizes, gra ...
Text characters embedded in images and video sequences represents a rich source of information for content-based indexing and retrieval applications. However, these text characters are difficult to be detected and recognized due to their various sizes, gra ...
Sequence recognition performance is often summarised first in terms of the number of hits (H), substitutions (S), deletions (D) and insertions (I), and then as a single statistic by the "word error rate" WER = 100(S D I)/(H S D). While in common use, WER h ...
This work presents categorization experiments performed over noisy texts. By noisy it is meant any text obtained through an extraction process (affected by errors) from media other than digital texts (e.g. transcriptions of speech recordings extracted with ...
This work presents document clustering experiments performed over noisy texts (i.e. text that have been extracted through an automatic process like speech or character recognition). The effect of recognition errors on different clustering techniques is mea ...
Spoken Document Retrieval (SDR) consists in retrieving segments of a speech database that are relevant to a query. The state-of-the-art approach to the SDR problem consists in transcribing the speech data into digital text before applying common Informatio ...
Text characters embedded in images and video sequences represents a rich source of information for content-based indexing and retrieval applications. However, these text characters are difficult to be detected and recognized due to their various sizes, gra ...
