In few-shot unsupervised domain adaptation (FS-UDA), most existing methods followed the learning (FSL) to leverage low-level local features (learned from conventional convolutional models, e.g., ResNet) for classification. However, goal of FS-UDA and FSL are relevant yet distinct, since aims classify samples in target rather than source domain. We found that insufficient FS-UDA, which could int...

In this paper, we propose an access control method with a secret key for semantic segmentation models the first time so that unauthorized users without cannot benefit from performance of trained models. The enables us not only to provide high authorized but also degrade users. We point out that, application segmentation, conventional methods which use encrypted images classification tasks are d...

In this paper, a multi-level image representation model is developed and used to mine semantic feature hidden in the original remote sensing image. This model is consisted of three levels : region level, region feature level and semantic level. The first two levels aim at represent image content by using region feature. Semantic level aims at extracting hidden semantic feature. At last, interes...

In this paper, we consider the problem of sentence difficulty analysis from various angles. Past works have endeavored to design deterministic scoring algorithms depending only on semantic and syntactic information. We propose instead not only to hire local feature space representing individual sentence with its syntactic and semantic structure, but also to consider global distributional differ...

Multiple grammatical and semantic features are adopted in content linking and argument/sentiment labeling for online forums in this paper. There are mainly two different methods for content linking. First, we utilize the deep feature obtained from Word Embedding Model in deep learning and compute sentence similarity. Second, we use multiple traditional features to locate candidate linking sente...

We address the problem of segmentation and recognition of sequences of multimodal human interactions in meetings. These interactions can be seen as a rough structure of a meeting, and can be used either as input for a meeting browser or as a first step towards a higher semantic analysis of the meeting. A common lexicon of multimodal group meeting actions, a shared meeting data set, and a common...

The undo mechanism is an essential feature in collaborative editing systems. Most popular semantic wikis support a revert feature, some provide an undo feature to remove any modification at any time. However this undo feature does not always succeed. Supporting the undo mechanism for P2P semantic wikis has never been tackled. In this paper, we present an undo approach for Swooki, the first P2P ...

Phishing is one of the luring techniques used to exploit personal information. A phishing webpage detection system (PWDS) extracts features to determine whether it is a phishing webpage or not. Selecting appropriate features improves the performance of PWDS. Performance criteria are detection accuracy and system response time. The major time consumed by PWDS arises from feature extraction that ...

In parsing with Tree Adjoining Grammar (TAG), independent derivations have been shown by Schabes and Shieber (1994) to be essential for correctly supporting syntactic analysis, semantic interpretation, and statistical language modeling. However, the parsing algorithm they propose is not directly applicable to Feature-Based TAGs (FB-TAG). We provide a recognition algorithm for FB-TAG that suppor...