scholarly journals Activity Recognition Using Gazed Text and Viewpoint Information for User Support Systems

2018 ◽  
Vol 7 (3) ◽  
pp. 31 ◽  
Author(s):  
Shun Chiba ◽  
Tomo Miyazaki ◽  
Yoshihiro Sugaya ◽  
Shinichiro Omachi
Keyword(s):  
Information Technology ◽  
Activity Recognition ◽  
Image Matching ◽  
Feature Vector ◽  
Support Systems ◽  
The Other ◽  
Recognition Method ◽  
Laboratory Environment ◽  
User Support ◽  
Fine Grained

The development of information technology has added many conveniences to our lives. On the other hand, however, we have to deal with various kinds of information, which can be a difficult task for elderly people or those who are not familiar with information devices. A technology to recognize each person’s activity and providing appropriate support based on that activity could be useful for such people. In this paper, we propose a novel fine-grained activity recognition method for user support systems that focuses on identifying the text at which a user is gazing, based on the idea that the content of the text is related to the activity of the user. It is necessary to keep in mind that the meaning of the text depends on its location. To tackle this problem, we propose the simultaneous use of a wearable device and fixed camera. To obtain the global location of the text, we perform image matching using the local features of the images obtained by these two devices. Then, we generate a feature vector based on this information and the content of the text. To show the effectiveness of the proposed approach, we performed activity recognition experiments with six subjects in a laboratory environment.

scholarly journals Learning Attentive Pairwise Interaction for Fine-Grained Classification

2020 ◽  
Vol 34 (07) ◽  
pp. 13130-13137 ◽  
Author(s):  
Peiqin Zhuang ◽  
Yali Wang ◽  
Yu Qiao
Keyword(s):  
Feature Vector ◽  
Interaction Network ◽  
Input Image ◽  
Pairwise Interaction ◽  
The Other ◽  
Challenging Problem ◽  
Fine Grained ◽  
Other Hand ◽  
Image Pairs ◽  
Individual Input

Fine-grained classification is a challenging problem, due to subtle differences among highly-confused categories. Most approaches address this difficulty by learning discriminative representation of individual input image. On the other hand, humans can effectively identify contrastive clues by comparing image pairs. Inspired by this fact, this paper proposes a simple but effective Attentive Pairwise Interaction Network (API-Net), which can progressively recognize a pair of fine-grained images by interaction. Specifically, API-Net first learns a mutual feature vector to capture semantic differences in the input pair. It then compares this mutual vector with individual vectors to generate gates for each input image. These distinct gate vectors inherit mutual context on semantic differences, which allow API-Net to attentively capture contrastive clues by pairwise interaction between two images. Additionally, we train API-Net in an end-to-end manner with a score ranking regularization, which can further generalize API-Net by taking feature priorities into account. We conduct extensive experiments on five popular benchmarks in fine-grained classification. API-Net outperforms the recent SOTA methods, i.e., CUB-200-2011 (90.0%), Aircraft (93.9%), Stanford Cars (95.3%), Stanford Dogs (90.3%), and NABirds (88.1%).

DEVELOPING THE SCIENTIFIC MAGAZINE IN THE PERIOD OF THE FOURTH INDUSTRIAL REVOLUTION 4.0

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Nguyen Duy Dung
Keyword(s):  
Artificial Intelligence ◽  
Information Technology ◽  
Industrial Revolution ◽  
Scientific Journal ◽  
Publishing Research ◽  
The Other ◽  
High Tech ◽  
Fourth Industrial Revolution ◽  
Socio Economic Development ◽  
International Scientific Journal

Characteristics of the industrial revolution 4.0 is the wide application of high-tech achievements, especially information technology, digitalization, artificial intelligence, network connections for management to create sudden changes in socio-economic development of many countries. Therefore, to reach the high-tech time, many magazines in Vietnam have changed dramatically, striving to reach the international scientific journal system of ISI, Scopus. The publication of international standard scientific journal will meet the demand of publishing research results of local scientists, on the other hand contribute to strengthening exchange, cooperation, international integration in science and technology.

scholarly journals Neutron Imaging Using a Fine-Grained Nuclear Emulsion

2021 ◽  
Vol 7 (1) ◽  
pp. 4
Author(s):  
Katsuya Hirota ◽  
Tomoko Ariga ◽  
Masahiro Hino ◽  
Go Ichikawa ◽  
Shinsuke Kawasaki ◽  
...  
Keyword(s):  
Image Analysis ◽  
High Resolution ◽  
Neutron Detector ◽  
Nuclear Emulsion ◽  
Neutron Imaging ◽  
The Other ◽  
Crystal Oscillator ◽  
Fine Grained ◽  
Cold Neutrons ◽  
Track Analysis

A neutron detector using a fine-grained nuclear emulsion has a sub-micron spatial resolution and thus has potential to be applied as high-resolution neutron imaging. In this paper, we present two approaches to applying the emulsion detectors for neutron imaging. One is using a track analysis to derive the reaction points for high resolution. From an image obtained with a 9 μm pitch Gd grating with cold neutrons, periodic peak with a standard deviation of 1.3 μm was observed. The other is an approach without a track analysis for high-density irradiation. An internal structure of a crystal oscillator chip, with a scale of approximately 30 μm, was able to be observed after an image analysis.

scholarly journals Facilitating fine-grained intra-urban dengue forecasting by integrating urban environments measured from street-view images

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Kang Liu ◽  
Ling Yin ◽  
Meng Zhang ◽  
Min Kang ◽  
Ai-Ping Deng ◽  
...  
Keyword(s):  
Machine Learning ◽  
High Risk ◽  
Feature Vector ◽  
Urban Environments ◽  
Environmental Feature ◽  
Fine Grained ◽  
Environmental Features ◽  
Street View ◽  
The City ◽  
Dengue Epidemic

Abstract Background Dengue fever (DF) is a mosquito-borne infectious disease that has threatened tropical and subtropical regions in recent decades. An early and targeted warning of a dengue epidemic is important for vector control. Current studies have primarily determined weather conditions to be the main factor for dengue forecasting, thereby neglecting that environmental suitability for mosquito breeding is also an important factor, especially in fine-grained intra-urban settings. Considering that street-view images are promising for depicting physical environments, this study proposes a framework for facilitating fine-grained intra-urban dengue forecasting by integrating the urban environments measured from street-view images. Methods The dengue epidemic that occurred in 167 townships of Guangzhou City, China, between 2015 and 2019 was taken as a study case. First, feature vectors of street-view images acquired inside each township were extracted by a pre-trained convolutional neural network, and then aggregated as an environmental feature vector of the township. Thus, townships with similar physical settings would exhibit similar environmental features. Second, the environmental feature vector is combined with commonly used features (e.g., temperature, rainfall, and past case count) as inputs to machine-learning models for weekly dengue forecasting. Results The performance of machine-learning forecasting models (i.e., MLP and SVM) integrated with and without environmental features were compared. This indicates that models integrating environmental features can identify high-risk urban units across the city more precisely than those using common features alone. In addition, the top 30% of high-risk townships predicted by our proposed methods can capture approximately 50–60% of dengue cases across the city. Conclusions Incorporating local environments measured from street view images is effective in facilitating fine-grained intra-urban dengue forecasting, which is beneficial for conducting spatially precise dengue prevention and control.

scholarly journals Global-Local Enhancement Network for NMF-Aware Sign Language Recognition

2021 ◽  
Vol 17 (3) ◽  
pp. 1-19
Author(s):  
Hezhen Hu ◽  
Wengang Zhou ◽  
Junfu Pu ◽  
Houqiang Li
Keyword(s):  
Sign Language ◽  
Daily Life ◽  
The Other ◽  
Challenging Problem ◽  
Language Recognition ◽  
Local Enhancement ◽  
Sign Language Recognition ◽  
Vocabulary Size ◽  
Hand Gestures ◽  
Fine Grained

Sign language recognition (SLR) is a challenging problem, involving complex manual features (i.e., hand gestures) and fine-grained non-manual features (NMFs) (i.e., facial expression, mouth shapes, etc .). Although manual features are dominant, non-manual features also play an important role in the expression of a sign word. Specifically, many sign words convey different meanings due to non-manual features, even though they share the same hand gestures. This ambiguity introduces great challenges in the recognition of sign words. To tackle the above issue, we propose a simple yet effective architecture called Global-Local Enhancement Network (GLE-Net), including two mutually promoted streams toward different crucial aspects of SLR. Of the two streams, one captures the global contextual relationship, while the other stream captures the discriminative fine-grained cues. Moreover, due to the lack of datasets explicitly focusing on this kind of feature, we introduce the first non-manual-feature-aware isolated Chinese sign language dataset (NMFs-CSL) with a total vocabulary size of 1,067 sign words in daily life. Extensive experiments on NMFs-CSL and SLR500 datasets demonstrate the effectiveness of our method.

scholarly journals I.—Microscopic Structure of Irish Granites. No. 2. Granite of Aillemore, Co. Mayo

1874 ◽  
Vol 1 (1) ◽  
pp. 1-2
Author(s):  
Edward Hull
Keyword(s):  
The Other ◽  
Microscopic Structure ◽  
South Side ◽  
North West ◽  
Fine Grained ◽  
Lower Silurian ◽  
The North ◽  
Geological Map ◽  
Vertical Walls ◽  
Dark Green

This granite forms an isolated mass, rising into two eminences a few miles south of Louisburg, called Corvock Brack (1287 feet) and Knockaskeheen (1288 feet). It is a greyish granite—generally fine—grained—consisting of quartz, two felspars,—one orthoclase, the other triclinic, probably oligoclase—and dark green mica. In some places there are patches in which the felspar assumes the appearance of “graphic granite.” Numerous boulders of this granite are strewn over the district to the north-west, and on the south side of Knockaskeheen; the rock is traversed by regular joints ranging N. 10 W., along which it splits off into nearly vertical walls. The position of the granite is shown on Griffith's Geological Map of Ireland, and it is surrounded by schistose beds, generally metamorphosed, and probably of Lower Silurian age. The granite itself is of older date than the Upper Llandovery beds, which lie to the southward.

Conditional Belief and the Ramsey Test

2002 ◽  
Vol 51 ◽  
pp. 215-232
Author(s):  
Scott Sturgeon
Keyword(s):  
Everyday Life ◽  
Common Sense ◽  
The Other ◽  
Coarse Grained ◽  
Degrees Of Belief ◽  
Conditional Belief ◽  
Ramsey Test ◽  
Fine Grained

Consider the frameS believes that—.Fill it with a conditional, sayIf you eat an Apple, you'll drink a Coke.what makes the result true? More generally, what facts are marked by instances ofS believes (A→C)?In a sense the answer is obious: beliefs are so marked. Yet that bromide leads directly to competing schools of thought. And the reason is simple.Common-sense thinks of belief two ways. Sometimes it sees it as a three-part affair. When so viewed either you believe, disbelieve, or suspend judgment. This take on belief is coarse-grained. It says belief has three flavours: acceptance, rejection, neither. But it's not the only way common-sense thinks of belief. Sometimes it's more subtle: ‘How strong is your faith?’ can be apposite between believers. That signals an important fact. Ordinary practice also treats belief as a fine-grained affair. It speaks of levels of confidence. It admits degrees of belief. It contains a fine-grained take as well. There are two ways belief is seen in everyday life. One is coarse-grained. The other is fine-grained.

scholarly journals Inferring object properties from human interaction and transferring them to new motions

2021 ◽  
Author(s):  
Qian Zheng ◽  
Weikai Wu ◽  
Hanting Pan ◽  
Niloy Mitra ◽  
Daniel Cohen-Or ◽  
...  
Keyword(s):  
Human Interaction ◽  
Strongly Correlated ◽  
Recognition Method ◽  
Fine Grained ◽  
Object Property ◽  
Correlated Motions ◽  
Object Properties ◽  
New Synthesis ◽  
Related Object ◽  
Highly Correlated

AbstractHumans regularly interact with their surrounding objects. Such interactions often result in strongly correlated motions between humans and the interacting objects. We thus ask: “Is it possible to infer object properties from skeletal motion alone, even without seeing the interacting object itself?” In this paper, we present a fine-grained action recognition method that learns to infer such latent object properties from human interaction motion alone. This inference allows us to disentangle the motion from the object property and transfer object properties to a given motion. We collected a large number of videos and 3D skeletal motions of performing actors using an inertial motion capture device. We analyzed similar actions and learned subtle differences between them to reveal latent properties of the interacting objects. In particular, we learned to identify the interacting object, by estimating its weight, or its spillability. Our results clearly demonstrate that motions and interacting objects are highly correlated and that related object latent properties can be inferred from 3D skeleton sequences alone, leading to new synthesis possibilities for motions involving human interaction. Our dataset is available at http://vcc.szu.edu.cn/research/2020/IT.html.

Nodular and other Keratophyres at St. Nicolas, Quebec

1971 ◽  
Vol 8 (1) ◽  
pp. 116-131
Author(s):  
F. Fitz Osborne ◽  
Paul Laroche
Keyword(s):  
The Other ◽  
Magmatic Origin ◽  
Fine Grained ◽  
Checker Board

Sills in Cambrian sandstone at two localities provide complementary evidence for the magmatic origin of keratophyres near St. Nicolas. The thickest sill has one facies whose solids at the time it was half or somewhat more crystallized had the composition of a hornblende laugenite. The rest magma at this stage gave rise to stellate and trachytoid keratophyre characterized by chlorite and checker-board albite with some quartz. At the other locality magma approximately of the composition of the stellate keratophyre was emplaced as sills up to 4 ft (1.2 m) thick and gave rise to medium-grained keratophyre with, along the selvages or within the sills, a fine-grained variety with chlorite and nodules, up to 1 in. (2.5 cm) diameter, of plagioclase. Illite or its precursor was secreted from the sills and was replaced by a network of veins with cores of quartz and spheroids of plagioclase, of chlorite, and of carbonate.

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