Placing Images with Refined Language Models and Similarity Search with PCA-reduced VGG Features
نویسندگان
چکیده
We describe the participation of the CERTH/CEA-LIST team in the MediaEval 2016 Placing Task. We submitted five runs to the estimation-based sub-task: one based only on text by employing a Language Model-based approach with several refinements, one based on visual content, using geospatial clustering over the most visually similar images, and three based on a hybrid scheme exploiting both visual and textual cues from the multimedia items, trained on datasets of different size and origin. The best results were obtained by a hybrid approach trained with external training data and using two publicly available gazetteers.
منابع مشابه
Ghent and Cardiff University at the 2012 Placing Task
We present the results of our submission to the MediaEval 2012 Placing Task. We used a framework that combines language models and similarity search, which improves our system from last year by using a different feature selection technique, extending our similarity search, tapping into new types of information for videos without any tags and including the use of SIFT features.
متن کاملClassification of Chest Radiology Images in Order to Identify Patients with COVID-19 Using Deep Learning Techniques
Background and Aim: Due to the important role of radiological images for identifying patients with COVID-19, creating a model based on deep learning methods was the main objective of this study. Materials and Methods: 15,153 available chest images of normal, COVID-19, and pneumonia individuals which were in the Kaggle data repository was used as dataset of this research. Data preprocessing inc...
متن کاملGhent University at the 2011 Placing Task
We present the results of a system that georeferences Flickr videos using a combination of language models and similarity search. The system extends our approach from last year by using language models with a more adaptive granularity, and by taking into account the home location of the user.
متن کاملUsing Text Surrounding Method to Enhance Retrieval of Online Images by Google Search Engine
Purpose: the current research aimed to compare the effectiveness of various tags and codes for retrieving images from the Google. Design/methodology: selected images with different characteristics in a registered domain were carefully studied. The exception was that special conceptual features have been apportioned for each group of images separately. In this regard, each group image surr...
متن کاملA Monte Carlo-Based Search Strategy for Dimensionality Reduction in Performance Tuning Parameters
Redundant and irrelevant features in high dimensional data increase the complexity in underlying mathematical models. It is necessary to conduct pre-processing steps that search for the most relevant features in order to reduce the dimensionality of the data. This study made use of a meta-heuristic search approach which uses lightweight random simulations to balance between the exploitation of ...
متن کامل