Attention Mechanism Based Semi-Supervised Multi-Gain Image Fusion
نویسندگان
چکیده
منابع مشابه
Graph-based multimodal semi-supervised image classification
We investigate an image classification task where training images come along with tags, but only a subset being labeled, and the goal is to predict the class label of test images without tags. This task is important for image search engine on photo sharing websites. In previous studies, it is handled by first training a multiple kernel learning classifier using both image content and tags to sc...
متن کاملMulti-view hac for Semi-supervised Document Image Classification
This paper presents a semi-supervised document image classification system that aims to be integrated into a commercial document reading software. This system is asserted like an annotation help. From a set of unknown document images given by a human operator, the system computes regrouping hypothesis of same physical layout images and proposes them to the operator. Then he can correct them, va...
متن کاملAttention-based Graph Neural Network for Semi-supervised Learning
Recently popularized graph neural networks achieve the state-of-the-art accuracy on a number of standard benchmark datasets for graph-based semi-supervised learning, improving significantly over existing approaches. These architectures alternate between a propagation layer that aggregates the hidden states of the local neighborhood and a fully-connected layer. Perhaps surprisingly, we show that...
متن کاملSemi-Supervised Multi-Task Regression
Labeled data are needed for many machine learning applications but the amount available in some applications is scarce. Semi-supervised learning and multi-task learning are two of the approaches that have been proposed to alleviate this problem. In this paper, we seek to integrate these two approaches for regression applications. We first propose a new supervised multi-task regression method ca...
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: Symmetry
سال: 2020
ISSN: 2073-8994
DOI: 10.3390/sym12030451