scholarly journals Random-Shaped Image Inpainting using Dilated Convolution

2019 ◽  
Vol 8 (6) ◽  
pp. 641-647
Keyword(s):  
Deep Learning ◽  
State Of The Art ◽  
Image Inpainting ◽  
Mean Value ◽  
Variable Size ◽  
Qualitative And Quantitative ◽  
The Past ◽  
New Novel ◽  
The Mean ◽  
Image Pixels

Over the past few years, Deep learning-based methods have shown encouraging and inspiring results for one of the most complex tasks of computer vision and image processing; Image Inpainting. The difficulty of image inpainting is derived from its’ need to fully and deeply understand of the structure and texture of images for producing accurate and visibly plausible results especially for the cases of inpainting a relatively larger region. Deep learning methods usually employ convolution neural network (CNN) for processing and analyzing images using filters that consider all image pixels as valid ones and usually use the mean value to substitute the missing pixels. This result in artifacts and blurry inpainted regions inconsistent with the rest of the image. In this paper, a new novel-based method is proposed for image inpainting of random-shaped missing regions with variable size and arbitrary locations across the image. We employed the use of dilated convolutions for composing multiscale context information without any loss in resolution as well as including a modification mask step after each convolution operation. The proposed method also includes a global discriminator that also considers the scale of patches as well as the whole image. The global discriminator is responsible for capturing local continuity of images texture as well as the overall global images’ features. The performance of the proposed method is evaluated using two datasets (Places2 and Paris Street View). Also, a comparison with the recent state-of-the-art is preformed to demonstrate and prove the effectiveness of our model in both qualitative and quantitative evaluations.

scholarly journals A Deep Multi-Frame Super-Resolution Network for Dynamic Scenes

2021 ◽  
Vol 11 (7) ◽  
pp. 3285
Author(s):  
Ze Pan ◽  
Zheng Tan ◽  
Qunbo Lv
Keyword(s):  
Deep Learning ◽  
Spatial Information ◽  
State Of The Art ◽  
Super Resolution ◽  
Dynamic Scenes ◽  
Qualitative And Quantitative ◽  
The Past ◽  
Spatial Alignment ◽  
Quantitative Analyses ◽  
Temporal And Spatial

The multi-frame super-resolution techniques have been prosperous over the past two decades. However, little attention has been paid to the combination of deep learning and multi-frame super-resolution. One reason is that most deep learning-based super-resolution methods cannot handle variant numbers of input frames. Another reason is that it is hard to capture accurate temporal and spatial information because of the misalignment of input images. To solve these problems, we propose an optical-flow-based multi-frame super-resolution framework, which is capable of dealing with various numbers of input frames. This framework enables to make full use of the input frames, allowing it to obtain better performance. In addition, we use a spatial subpixel alignment module for more accurate subpixel-wise spatial alignment and introduce a dual weighting module to generate weights for temporal fusion. Both two modules lead to more effective and accurate temporal fusion. We compare our method with other state-of-the-art methods and conduct ablation studies on our method. The results of qualitative and quantitative analyses show that our method achieves state-of-the-art performances, demonstrating the advantage of the designed framework and the necessity of proposed modules.

Vesseg: An Open-Source Tool for Deep Learning-Based Atherosclerotic Plaque Quantification in Histopathology Image

2021 ◽  
Author(s):  
J.M. Murray ◽  
P. Pfeffer ◽  
R. Seifert ◽  
A. Hermann ◽  
J. Handke ◽  
...  
Keyword(s):  
Deep Learning ◽  
Open Source ◽  
Atherosclerotic Plaque ◽  
State Of The Art ◽  
The Mean ◽  
Time Savings ◽  
Plaque Quantification ◽  
Atherosclerosis Research ◽  
Hematoxylin Eosin ◽  
Microscopy Images

Objective: Manual plaque segmentation in microscopy images is a time-consuming process in atherosclerosis research and potentially subject to unacceptable user-to-user variability and observer bias. We address this by releasing Vesseg a tool that includes state-of-the-art deep learning models for atherosclerotic plaque segmentation. Approach and Results: Vesseg is a containerized, extensible, open-source, and user-oriented tool. It includes 2 models, trained and tested on 1089 hematoxylin-eosin stained mouse model atherosclerotic brachiocephalic artery sections. The models were compared to 3 human raters. Vesseg can be accessed at https://vesseg .online or downloaded. The models show mean Soerensen-Dice scores of 0.91±0.15 for plaque and 0.97±0.08 for lumen pixels. The mean accuracy is 0.98±0.05. Vesseg is already in active use, generating time savings of >10 minutes per slide. Conclusions: Vesseg brings state-of-the-art deep learning methods to atherosclerosis research, providing drastic time savings, while allowing for continuous improvement of models and the underlying pipeline.

scholarly journals Complex Data Imputation by Auto-Encoders and Convolutional Neural Networks—A Case Study on Genome Gap-Filling

Computers ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 37 ◽  
Author(s):  
Luca Cappelletti ◽  
Tommaso Fontana ◽  
Guido Walter Di Donato ◽  
Lorenzo Di Tucci ◽  
Elena Casiraghi ◽  
...  
Keyword(s):  
Deep Learning ◽  
Missing Data ◽  
State Of The Art ◽  
The State ◽  
Complex Data ◽  
Data Imputation ◽  
Genome Sequences ◽  
Missing Data Imputation ◽  
The Past ◽  
Learning Techniques

Missing data imputation has been a hot topic in the past decade, and many state-of-the-art works have been presented to propose novel, interesting solutions that have been applied in a variety of fields. In the past decade, the successful results achieved by deep learning techniques have opened the way to their application for solving difficult problems where human skill is not able to provide a reliable solution. Not surprisingly, some deep learners, mainly exploiting encoder-decoder architectures, have also been designed and applied to the task of missing data imputation. However, most of the proposed imputation techniques have not been designed to tackle “complex data”, that is high dimensional data belonging to datasets with huge cardinality and describing complex problems. Precisely, they often need critical parameters to be manually set or exploit complex architecture and/or training phases that make their computational load impracticable. In this paper, after clustering the state-of-the-art imputation techniques into three broad categories, we briefly review the most representative methods and then describe our data imputation proposals, which exploit deep learning techniques specifically designed to handle complex data. Comparative tests on genome sequences show that our deep learning imputers outperform the state-of-the-art KNN-imputation method when filling gaps in human genome sequences.

scholarly journals Development of Jawi Spelling Skills Mobile Applications, 'Oh Jawiku'

2019 ◽  
Vol 13 (07) ◽  
pp. 80
Author(s):  
Noor Asmina Binti Mohd Rashid ◽  
Shaharuddin Bin Md Salleh ◽  
Norah Binti Md Noor
Keyword(s):  
Mobile Learning ◽  
Mobile Applications ◽  
Mobile Application ◽  
Mean Value ◽  
The Past ◽  
Post Test ◽  
Main Medium ◽  
The Mean ◽  
Addie Model ◽  
Roman Script

<p class="0abstract"> In the past, Jawi script was the main medium of intermediation in Malaya. However, since the emergence of the Roman script, the use of Jawi script has been marginalized causing less awareness among some of the younger generation on the uniqueness of Jawi script. Therefore, a mobile application has been developed to attract students to explore Jawi script especially the spelling of Jawi words. This Jawi Spelling Skills mobile application used constructivism approach and ADDIE model during the development process. This study used quantitative one group pre-test and post-test research design that conducted among 20 students of a primary school. The result shows that the mean value of the post-test was higher than the pre-test which is 89.00 while the percentage of students who liked the Jawi Spelling Skills mobile learning application was high. In conclusion, the application of Jawi Spelling Skills Mobile Learning Application able to attract students to learn Jawi indirectly raised the dignity of Jawi script in the future besides supporting the 21st- century education.</p>

scholarly journals Assessment of the TMJ Dysfunction Using the Computerized Facebow Analysis of Selected Parameters

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Edward Kijak ◽  
Danuta Lietz-Kijak ◽  
Bogumiła Frączak ◽  
Zbigniew Śliwiński ◽  
Jerzy Margielewicz
Keyword(s):  
Age Groups ◽  
Mouth Opening ◽  
Mean Value ◽  
Qualitative And Quantitative Analysis ◽  
Temporomandibular Joint Dysfunction ◽  
Mean Values ◽  
Qualitative And Quantitative ◽  
Maximum Value ◽  
Function Test ◽  
The Mean

The Purpose of the Paper.Qualitative and quantitative analysis of selected parameters of mandible movements, electronically registered in patients with temporomandibular joint dysfunction and healthy ones.Material. Function test of the mandible movements was conducted in 175 patients. Gender distribution was 143 women and 32 men, aged 9 to 84.Methods. The studied population, after accurate clinical examination, was divided into age groups with the range of five years. All the patients had Zebris JMA computerized facebow examination done, according to the generally accepted principles and procedures.Results.Mean values of mouth opening calculated to 45.6 mm in healthy group and 37.6 mm in TMJ dysfunction group. Mean length of condylar path amounted to39±7% of the maximum value of mouth opening in the group of healthy people,44±11% in the case of muscle-based disorders, and35±11% with joint-based. The mean value of the condylar path inclination oscillated in the range of 25° to 45°.Conclusions. The ratio of length of the condylar path to the size of mouth opening may be a significant value characterising the type and degree of intensification of the TMJ dysfunctions.

Non-Linear Model of Rubber Bearings under Random Excitation

2012 ◽  
Vol 452-453 ◽  
pp. 602-606
Author(s):  
Hai Yan Jing ◽  
Yan Ping Zheng ◽  
Ming Xia Fang
Keyword(s):  
Past Research ◽  
Random Excitation ◽  
Mean Value ◽  
Statistical Characteristics ◽  
The Past ◽  
Non Linear ◽  
The Mean ◽  
Rubber Bearings ◽  
Force Displacement ◽  
Sinusoidal Excitation

Through dynamics test and theoretical analysis about rubber bearings in Auto body’s sub-frame, and the past research results of sinusoidal excitation, a hysteretic non-linear mathematical model of the rubber bearings is established under the condition of random excitation. The model shows that the hysteretic renewed force of the rubber bearings under random excitation can be expressed with the mean value and variance of random excitation’s statistical characteristics and speed. Finally curves of the hysteretic renewed force - displacement are reconstructed with the model built, which match the test’s results well.

scholarly journals Characteristics of cold–warm variation in the Hetao region and its surrounding areas in China during the past 5000 years

2010 ◽  
Vol 6 (4) ◽  
pp. 475-481 ◽  
Author(s):  
M.-Q. Li ◽  
Q.-S. Ge ◽  
Z.-X. Hao ◽  
J.-Y. Zheng ◽  
S.-F. He
Keyword(s):  
Climate Changes ◽  
Mean Value ◽  
Data Series ◽  
Proxy Data ◽  
Average Temperature ◽  
The Past ◽  
The Mean ◽  
Temperature Proxy ◽  
Surrounding Areas

Abstract. Using six long-term temperature proxy data series derived from different natural evidences, including pollens and lake-sediments, we reconstructed a temperature series with a 100-yr time resolution for the past 5000 yr in the Hetao region and its surrounding areas. The resulting series suggests that, on a millennial timescale, temperatures in the region were higher than the mean value of the whole series during the 5000~2600 years before present (yr BP) period, and became relatively low comparing with the average temperature of the whole series after 2600 yr BP. Within these two periods, temperature fluctuations comprising numerous short, multi-centennial intervals also existed. A comparison between our reconstructed series and other series in China and across the Northern Hemisphere indicate that, on a long-term scale, cold–warm variations had been in phase across the whole hemisphere during the past 5000 years; on the century to multi-century scale, the beginning and the ending times varied from region to region, thus implying that climate changes did not occur simultaneously in different regions.

scholarly journals Comparative analysis of maternal mortality indices in Perm Krai over the past 20 years

2018 ◽  
Vol 35 (5) ◽  
pp. 57-62
Author(s):  
M. M. Padrul ◽  
E. V. Cherkasova ◽  
V. V. Skryabina ◽  
S. N. Berseneva
Keyword(s):  
Comparative Analysis ◽  
Maternal Mortality ◽  
Statistical Data ◽  
Federal District ◽  
Mean Value ◽  
Data Intensive ◽  
The Past ◽  
Perm Krai ◽  
The Russian Federation ◽  
The Mean

Aim. To compare the maternal mortality (MM) indices in Perm Krai with MM indices in the Russian Federation (RF) and Privolzhskiy Federal District over the past 20 years. Materials and methods. On the basis of official statistical data, intensive indices and image indices, mean multiyear MM indices, 95 % confidence intervals, median, 25 and 75 percentile indices were calculated. The mean multiyear indices are presented as M (mean value) ± SD (standard deviation). Results. According to official statistical data, the mean multiyear (1997–2016) indices of MM coefficient in Perm Krai tend to decline, but they do not reliably differ from the analogous indices in RF. During the last 20 years, there was noted a steady and obvious decrease in MM index on the territory of Perm Krai, especially marked for the last 2 years (2015–2016) that resulted in appearance of statistically significant differences regarding this index in Perm Krai compared to these indices in RF as a whole. Conclusions. Perm Krai is a rather favorable region as far as rendering of medical aid to pregnant, parturient women and puerperas is concerned.

scholarly journals Global and Local Attention-Based Free-Form Image Inpainting

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3204
Author(s):  
S. M. Nadim Uddin ◽  
Yong Ju Jung
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Convolutional Neural Network ◽  
State Of The Art ◽  
Image Inpainting ◽  
Experimental Results ◽  
Free Form ◽  
Local Similarity ◽  
Global And Local ◽  
Similarity Information

Deep-learning-based image inpainting methods have shown significant promise in both rectangular and irregular holes. However, the inpainting of irregular holes presents numerous challenges owing to uncertainties in their shapes and locations. When depending solely on convolutional neural network (CNN) or adversarial supervision, plausible inpainting results cannot be guaranteed because irregular holes need attention-based guidance for retrieving information for content generation. In this paper, we propose two new attention mechanisms, namely a mask pruning-based global attention module and a global and local attention module to obtain global dependency information and the local similarity information among the features for refined results. The proposed method is evaluated using state-of-the-art methods, and the experimental results show that our method outperforms the existing methods in both quantitative and qualitative measures.

scholarly journals Relationship between atopic manifestations, family history of atopic disease and cord blood IgE levels in children

2007 ◽  
Vol 47 (6) ◽  
pp. 278
Author(s):  
Tisnasari Hafsah ◽  
Myrna Soepriadi ◽  
Budi Setiabudiawan ◽  
Herry Garna
Keyword(s):  
Family History ◽  
Cord Blood ◽  
Atopic Disease ◽  
Mean Value ◽  
Inclusion Criteria ◽  
Chi Square ◽  
The Past ◽  
History Of ◽  
The Mean ◽  
The Relationship

Background The incidence of atopic disease tends to increaseover the past few decades and its morbidity interferes with thequality of life and health. Prediction of the disease is importantfor early prevention.Objective To evaluate the relationship between atopicmanifestations, family history (FH) of atopic disease and cordblood IgE (CB-IgE) levels.Methods We conducted an analytic observational study withcohort retrospective design on children with an average age of 3years whose CB-IgE had been measured at delivery inKiaracondong Primary Health Care during October–December2004. Manifestations of atopic disease were recorded using ISAACquestionaire for allergy. Chi-square, Mann-Whitney test, andlogistic regression analysis were used for analysis.Results Cord blood IgE was measured on 124 children after birth.Only 94 children (76%) fulfilled the inclusion criteria. Atopicdisease was found in 17 children (18%), consisting of 8 childrenwith atopic dermatitis, 4 with allergic rhinitis, and 5 suffered fromboth. There were significant differences in the mean value of CB-IgE (Z M-W =4.60; P<0.001) and FH (x 2 =19.059; P<0.001)between atopic and non atopic children. Cut off point of the CB-IgE concentration was 1.4 IU/mL (77.7%). The highest probabilityfor atopic manifestations was found in children who had highCB-IgE and positive FH (P=45%). Relative risk of children withhigh CB-IgE level in positive FH group was 3.636 (95% CI0.943;14.016).Conclusion CB-IgE level and family history of atopic disease arerisk factors for the development of atopic manifestation.

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