En este artículo proporcionamos una descripción general del hash sensible a la ubicación (LSH) utilizado para la recuperación de imágenes a gran escala y para resolver el problema del vecino más cercano. El objetivo es experimentar con diferentes configuraciones de parámetros de LSH sobre un conjunto de huellas dactilares de video para ver cuál es la mejor en términos de precisión e indexación para que luego, dado un objeto de consulta, devuelva los objetos (vecinos más cercanos) que sean más similares a la consulta. Los parámetros de configuración que ofrecieron mejores resultados fueron un tamaño de cubo de 24 con 15 tablas y tamaños de hash de 15 bits, obteniendo aproximadamente el 50% de las coincidencias correctas con los métodos de re...
Locality-Sensitive Hashing (LSH) is widely used to solve approximate nearest neighbor search problem...
Efficient high-dimensional similarity search structures are essential for building scalable content-...
Locality Sensitive Hashing (LSH) is one of the most promising techniques for solving nearest neighbo...
En este artículo proporcionamos una descripción general del hash sensible a la ubicación (LSH) utili...
International audienceIt is well known that high-dimensional nearest-neighbor retrieval is very expe...
International audienceIt is well known that high-dimensional nearest-neighbor retrieval is very expe...
International audienceThis paper presents a comparative experimental study of the multidimensional i...
Searching for similar video clips in large video database, or video identification, requires finding...
Similarity search is a key challenge for multimedia retrieval applications where data are usually re...
It is well known that high-dimensional nearest neighbor retrieval is very expensive. Many signal pro...
Abstract—Similarity search is critical for many database ap-plications, including the increasingly p...
We propose a novel hashing-based matching scheme, called Locally Optimized Hashing (LOH), based on ...
One key challenge in content-based image retrieval (CBIR) is to develop a fast solution for indexing...
Many modern applications of AI such as web search, mobile browsing, image processing, and natural la...
[ES] Las técnicas de hashing se han vuelto muy populares a la hora de resolver problemas de recupera...
Locality-Sensitive Hashing (LSH) is widely used to solve approximate nearest neighbor search problem...
Efficient high-dimensional similarity search structures are essential for building scalable content-...
Locality Sensitive Hashing (LSH) is one of the most promising techniques for solving nearest neighbo...
En este artículo proporcionamos una descripción general del hash sensible a la ubicación (LSH) utili...
International audienceIt is well known that high-dimensional nearest-neighbor retrieval is very expe...
International audienceIt is well known that high-dimensional nearest-neighbor retrieval is very expe...
International audienceThis paper presents a comparative experimental study of the multidimensional i...
Searching for similar video clips in large video database, or video identification, requires finding...
Similarity search is a key challenge for multimedia retrieval applications where data are usually re...
It is well known that high-dimensional nearest neighbor retrieval is very expensive. Many signal pro...
Abstract—Similarity search is critical for many database ap-plications, including the increasingly p...
We propose a novel hashing-based matching scheme, called Locally Optimized Hashing (LOH), based on ...
One key challenge in content-based image retrieval (CBIR) is to develop a fast solution for indexing...
Many modern applications of AI such as web search, mobile browsing, image processing, and natural la...
[ES] Las técnicas de hashing se han vuelto muy populares a la hora de resolver problemas de recupera...
Locality-Sensitive Hashing (LSH) is widely used to solve approximate nearest neighbor search problem...
Efficient high-dimensional similarity search structures are essential for building scalable content-...
Locality Sensitive Hashing (LSH) is one of the most promising techniques for solving nearest neighbo...