Search Results for author:
Found 6 papers, 3 papers with code
A location-aware embedding technique for accurate landmark recognition
The current state of the research in landmark recognition highlights the good accuracy which can be achieved by embedding techniques, such as Fisher vector and VLAD.
Efficient Nearest Neighbors Search for Large-Scale Landmark Recognition
It allows to drastically reduce the query time and outperforms the accuracy results compared to the state-of-the-art methods for large-scale landmark recognition.
An accurate retrieval through R-MAC+ descriptors for landmark recognition
The landmark recognition problem is far from being solved, but with the use of features extracted from intermediate layers of Convolutional Neural Networks (CNNs), excellent results have been obtained.
A Dense-Depth Representation for VLAD descriptors in Content-Based Image Retrieval
The recent advances brought by deep learning allowed to improve the performance in image retrieval tasks.
An Efficient Approximate kNN Graph Method for Diffusion on Image Retrieval
The application of the diffusion in many computer vision and artificial intelligence projects has been shown to give excellent improvements in performance.
Genetic Algorithms for the Optimization of Diffusion Parameters in Content-Based Image Retrieval
We propose to use genetic algorithms to find the optimal setting of all the diffusion parameters with respect to retrieval performance for each different dataset.
