Learning a Hierarchical Global Attention for Image Classification
نویسندگان
چکیده
منابع مشابه
Robust Method for E-Maximization and Hierarchical Clustering of Image Classification
We developed a new semi-supervised EM-like algorithm that is given the set of objects present in eachtraining image, but does not know which regions correspond to which objects. We have tested thealgorithm on a dataset of 860 hand-labeled color images using only color and texture features, and theresults show that our EM variant is able to break the symmetry in the initial solution. We compared...
متن کاملA Hierarchical Classification Method for Breast Tumor Detection
Introduction Breast cancer is the second cause of mortality among women. Early detection of it can enhance the chance of survival. Screening systems such as mammography cannot perfectly differentiate between patients and healthy individuals. Computer-aided diagnosis can help physicians make a more accurate diagnosis. Materials and Methods Regarding the importance of separating normal and abnorm...
متن کاملLarge margin learning of hierarchical semantic similarity for image classification
In the present paper, a novel image classification method that uses the hierarchical structure of categories to produce more semantic prediction is presented. This implies that our algorithm may not yield a correct prediction, but the result is likely to be semantically close to the right category. Therefore, the proposed method is able to provide a more informative classification result. The m...
متن کاملHierarchical Metric Learning for Fine Grained Image Classification
This paper deals with the problem of fine-grained image classification and introduces the notion of hierarchical metric learning for the same. It is indeed challenging to categorize fine-grained image classes merely in terms of a single level classifier given the subtle inter-class visual differences. In order to tackle this problem, we propose a two stage framework where i) the image categorie...
متن کاملHierarchical Attention Networks for Document Classification
We propose a hierarchical attention network for document classification. Our model has two distinctive characteristics: (i) it has a hierarchical structure that mirrors the hierarchical structure of documents; (ii) it has two levels of attention mechanisms applied at the wordand sentence-level, enabling it to attend differentially to more and less important content when constructing the documen...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Future Internet
سال: 2020
ISSN: 1999-5903
DOI: 10.3390/fi12110178