scholarly journals Face Swapping Consistency Transfer with Neural Identity Carrier

2021 ◽  
Vol 13 (11) ◽  
pp. 298
Author(s):  
Kunlin Liu ◽  
Ping Wang ◽  
Wenbo Zhou ◽  
Zhenyu Zhang ◽  
Yanhao Ge ◽  
...  
Keyword(s):  
Identity Transformation ◽  
Detection Methods ◽  
Facial Structure ◽  
Identity Information ◽  
Fine Grained ◽  
Uncertainty Prediction ◽  
3D Geometry ◽  
Original Frame

Deepfake aims to swap a face of an image with someone else’s likeness in a reasonable manner. Existing methods usually perform deepfake frame by frame, thus ignoring video consistency and producing incoherent results. To address such a problem, we propose a novel framework Neural Identity Carrier (NICe), which learns identity transformation from an arbitrary face-swapping proxy via a U-Net. By modeling the incoherence between frames as noise, NICe naturally suppresses its disturbance and preserves primary identity information. Concretely, NICe inputs the original frame and learns transformation supervised by swapped pseudo labels. As the temporal incoherence has an uncertain or stochastic pattern, NICe can filter out such outliers and well maintain the target content by uncertainty prediction. With the predicted temporally stable appearance, NICe enhances its details by constraining 3D geometry consistency, making NICe learn fine-grained facial structure across the poses. In this way, NICe guarantees the temporal stableness of deepfake approaches and predicts detailed results against over-smoothness. Extensive experiments on benchmarks demonstrate that NICe significantly improves the quality of existing deepfake methods on video-level. Besides, data generated by our methods can benefit video-level deepfake detection methods.

scholarly journals Benchmarking Unsupervised Outlier Detection with Realistic Synthetic Data

2021 ◽  
Vol 15 (4) ◽  
pp. 1-20
Author(s):  
Georg Steinbuss ◽  
Klemens Böhm
Keyword(s):  
Outlier Detection ◽  
Synthetic Data ◽  
Real Data ◽  
Detection Methods ◽  
Quality Of Data ◽  
Benchmark Data ◽  
Core Idea ◽  
Generic Process ◽  
Unsupervised Outlier Detection

Benchmarking unsupervised outlier detection is difficult. Outliers are rare, and existing benchmark data contains outliers with various and unknown characteristics. Fully synthetic data usually consists of outliers and regular instances with clear characteristics and thus allows for a more meaningful evaluation of detection methods in principle. Nonetheless, there have only been few attempts to include synthetic data in benchmarks for outlier detection. This might be due to the imprecise notion of outliers or to the difficulty to arrive at a good coverage of different domains with synthetic data. In this work, we propose a generic process for the generation of datasets for such benchmarking. The core idea is to reconstruct regular instances from existing real-world benchmark data while generating outliers so that they exhibit insightful characteristics. We propose and describe a generic process for the benchmarking of unsupervised outlier detection, as sketched so far. We then describe three instantiations of this generic process that generate outliers with specific characteristics, like local outliers. To validate our process, we perform a benchmark with state-of-the-art detection methods and carry out experiments to study the quality of data reconstructed in this way. Next to showcasing the workflow, this confirms the usefulness of our proposed process. In particular, our process yields regular instances close to the ones from real data. Summing up, we propose and validate a new and practical process for the benchmarking of unsupervised outlier detection.

Navigational Data Change Detection Based on Rasterizing Features & Attributes

2012 ◽  
Vol 256-259 ◽  
pp. 2279-2284
Author(s):  
Lian Ying Li ◽  
Zhang Huang ◽  
Xiao Lan Xu
Keyword(s):  
Change Detection ◽  
Detection Methods ◽  
Vehicle Navigation ◽  
Digital Map ◽  
Navigation Data ◽  
Data Production ◽  
History Of ◽  
Map Data ◽  
Data Updating

A necessary updating degree is vital for the digital map data in a vehicle navigation system. Only when the digital map data are well updated, can the quality of the navigation be assured. Today the companies devoting to the production of digital map data for vehicle navigation have to cost much labor, material and capital to collect and update data in order to maintain a necessary updating degree. Throughout the history of electronic navigation data updating, they have made considerable progress both on the methods and processes of data production, and the way of map management. Updating from the CD to the network, from the wired to the wireless, from the replacing to the incremental way, each of the technical changes is a power source to enhance the data updating rate. As we all know, the change detection is a prerequisite and base for the electronic navigation data updating. By rapidly developing the area with changes and using the appropriate updating method, we can scientifically maintain the original database of navigation data and terminal physical data. In view of this, starting from application needs for dynamic data updating, this paper analyses change detection methods of navigation data in different versions used for generating incremental data, and focuses on that of rasterizing features and attributes, exploring a new approach to quickly get the incremental data between versions.

scholarly journals Monitoring Skeletal Anomalies in Big-Scale Sand Smelt, Atherina boyeri, as a Potential Complementary Tool for Early Detection of Effects of Anthropic Pressure in Coastal Lagoons

Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 159
Author(s):  
Chiara Leone ◽  
Francesca De Luca ◽  
Eleonora Ciccotti ◽  
Arianna Martini ◽  
Clara Boglione
Keyword(s):  
Early Detection ◽  
Habitat Degradation ◽  
Anthropogenic Impacts ◽  
Coastal Lagoons ◽  
Ecological Status ◽  
Detection Methods ◽  
Anthropogenic Pressures ◽  
Morphological Examination ◽  
Skeletal Anomalies

Mediterranean coastal lagoons are increasingly affected by several threats, all concurrently leading to habitat degradation and loss. Methods based on fish for the assessment of the ecological status are under implementation for the Water Framework Directive requirements, to assess the overall quality of coastal lagoons. Complementary tools based on the use of single fish species as biological indicators could be useful as early detection methods of anthropogenic impacts. The analysis of skeletal anomalies in the big-scale sand smelt, Atherina boyeri, from nine Mediterranean coastal lagoons in Italy was carried out. Along with the morphological examination of fish, the environmental status of the nine lagoons was evaluated using a method based on expert judgement, by selecting and quantifying several environmental descriptors of direct and indirect human pressures acting on lagoon ecosystems. The average individual anomaly load and the frequency of individuals with severe anomalies allow to discriminate big-scale sand smelt samples on the basis of the site and of its quality status. Furthermore, a relationship between skeletal anomalies and the environmental quality of specific lagoons, driven by the anthropogenic pressures acting on them, was found. These findings support the potentiality of skeletal anomalies monitoring in big-scale sand smelt as a tool for early detection of anthropogenic impacts in coastal lagoons of the Mediterranean region.

The Study on High Precision 3D Detection Method of Steel Plate Surface Based on Structured Light

2012 ◽  
Vol 572 ◽  
pp. 338-342 ◽  
Author(s):  
Zhi Guo Liang ◽  
Quan Yang ◽  
Ke Xu ◽  
Fei He ◽  
Xiao Chen Wang ◽  
...  
Keyword(s):  
Surface Quality ◽  
Steel Plate ◽  
Detection Method ◽  
Structured Light ◽  
Detection Methods ◽  
Measurement Technology ◽  
Detection Accuracy ◽  
Plate Surface ◽  
Factors Affecting

Structured light 3D measurement technology with its simple structure, non-contact measurement, fast measurement speed and other advantages, has been widely used. Steel plate surface quality detection is not confined to the two-dimensional feature of gray detection, and local topography measurement for surface quality of steel plate detection becomes increasingly important. In this paper, steel plate surface 3D detection method based on structured light and the factors affecting the measurement accuracy are analyzed. Several effective methods of improving 3D detection accuracy are put forward. Compared with the traditional structured light 3D detection methods, the detection accuracy of new methods is remarkably improved, thus possessing better application values.

scholarly journals Analysis of Detection and Treatment Schemes of Highway Tunnel Lining Cracks

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Yike Wei ◽  
Lingfeng Yu
Keyword(s):  
Daily Life ◽  
Tunnel Lining ◽  
Detection Methods ◽  
Tunnel Engineering ◽  
Highway Tunnel ◽  
People’S Daily ◽  
People's Daily

Highway tunnels play a very important role in people's daily life. Among them, lining is an essential part of tunnel engineering, and the quality of lining greatly affects the overall quality of the tunnel. On this basis, the causes of lining cracks and the detection methods of existing highway tunnel lining cracks are analyzed, and the treatment countermeasures for highway tunnel lining cracks are proposed.

scholarly journals A common goal to CARE: Cancer Advocates, Researchers, and Clinicians Explore current treatments and clinical trials for breast cancer brain metastases

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Natalie S. Joe ◽  
Christine Hodgdon ◽  
Lianne Kraemer ◽  
Kristin J. Redmond ◽  
Vered Stearns ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Clinical Trials ◽  
Brain Metastases ◽  
Detection Methods ◽  
Future Research ◽  
Breast Cancer Brain Metastasis ◽  
Patient Advocates ◽  
Breast Cancer Brain Metastases ◽  
The Brain

AbstractBreast cancer is the most commonly diagnosed cancer in women worldwide. Approximately one-tenth of all patients with advanced breast cancer develop brain metastases resulting in an overall survival rate of fewer than 2 years. The challenges lie in developing new approaches to treat, monitor, and prevent breast cancer brain metastasis (BCBM). This review will provide an overview of BCBM from the integrated perspective of clinicians, researchers, and patient advocates. We will summarize the current management of BCBM, including diagnosis, treatment, and monitoring. We will highlight ongoing translational research for BCBM, including clinical trials and improved detection methods that can become the mainstay for BCBM treatment if they demonstrate efficacy. We will discuss preclinical BCBM research that focuses on the intrinsic properties of breast cancer cells and the influence of the brain microenvironment. Finally, we will spotlight emerging studies and future research needs to improve survival outcomes and preserve the quality of life for patients with BCBM.

scholarly journals Quality of life among ovarian cancer survivors in Haji Adam Malik General Hospital Medan, Indonesia

2020 ◽  
Vol 11 (2) ◽  
pp. 133-139
Author(s):  
Kristivani Br Ginting ◽  
Muhammad Rizki Yaznil ◽  
M. Oky Prabudi ◽  
Lili Rahmawati
Keyword(s):  
Quality Of Life ◽  
Ovarian Cancer ◽  
Cancer Survivors ◽  
General Hospital ◽  
Detection Methods ◽  
Cross Sectional ◽  
Eortc Qlq C30 ◽  
C 30 ◽  
Eortc Qlq

Latar belakang: Kanker ovarium memiliki angka mortalitas yang cukup tinggi dikarenakan gejalanya yang tidak spesifik, sering ditemukan pada stadium lanjut, dan belum adanya metode deteksi dini yang sudah terbukti. Untuk menilai keberhasilan terapi penyintas kanker ovarium, tidak hanya dinilai dari aspek klinis tetapi juga dinilai dari kualitas hidup penyintas kanker ovarium yang penilaiannya berdasarkan skala fungsional dan skala gejala dalam kuesioner EORTC QLQ C30 dan EORTC QLQ OV28. Metode: Penelitian ini menggunakan desain penelitian cross sectional, menggunakan data primer dari hasil wawancara dengan kuesioner EORTC QLQ C30 dan EORTC QLQ OV28 serta data sekunder yang berasal dari rekam medik di RSUP Haji Adam Malik Medan tahun 2017 - 2018. Sampel penelitian dipilih dengan metode total sampling dari seluruh data rekam medik yang memenuhi kriteria penelitian.   Hasil: Hasil penelitian ini didapatkan kualitas hidup global penyintas kanker ovarium 89.36% adalah baik, dan 10.64% adalah sedang serta tidak ada yang memiliki kualitas hidup buruk. Namun, didapatkan adanya gangguan pada skala fungsional berupa: fungsi emosional, fungsi kognitif, fungsi seksual, dan sikap terhadap penyakit, serta adanya permasalahan pada skala gejala berupa: kelelahan, nyeri, neuropati perifer, dan gejala menopause. Didapatkan juga tidak ada hubungan karakteristik usia, jenis histopatologis, stadium, lama terapi dengan kualitas hidup penyintas kanker ovarium, namun terdapat hubungan antara jenis terapi dengan kualitas hidup penyintas kanker ovarium. Kesimpulan: Kualitas hidup penyintas kanker ovarium secara global adalah baik. Kata Kunci: Kualitas Hidup, Penyintas Kanker Ovarium, EORTC QLQ C-30, EORTC QLQ     OV-28   Abstract Background: Ovarian cancer has a high mortality rate due to nonspecific symptoms, often found at an advanced stage, and also the absence of proven early detection methods. To assess the success of ovarian cancer survivors therapy, it is not only assessed from the clinical aspect but also from the quality of life of ovarian cancer survivors which is based on the functional and symptom scale in the EORTC QLQ C30 and EORTC QLQ OV28 questionnaires.  Methods: This study used a cross-sectional study design, using primary data from interviews with the survivors based on the questionnaire EORTC QLQ C30 and EORTC QLQ OV28 as well as secondary data derived from medical records at Haji Adam Malik General Hospital Medan in 2017 - 2018. The research sample was used with a total sampling method from all medical record data that fulfill the research criteria.  Result: The quality of life of ovarian cancer survivors is generally good (89.36%), meanwhile the rest is moderate (10.64%) without the poor quality of life. However, there are disorders on the functional scale in the form of emotional function, cognitive function, sexual function, and attitude toward disease. Likewise on the scale of symptoms, there are problems including: fatigue, pain, peripheral neuropathy, and menopausal symptoms.  Conclusion: The quality of life of ovarian cancer survivors globally is good. Keywords: Quality of Life, Ovarian Cancer Survivors, EORTC QLQ C-30, EORTC QLQ OV-28  

scholarly journals Loneliness and social interaction dynamics: An ambulatory assessment study in a student population

2021 ◽  
Author(s):  
Timon Elmer ◽  
Gerine M. A. Lodder
Keyword(s):  
Social Interaction ◽  
Social Interactions ◽  
Social Relationships ◽  
Sensor Data ◽  
Ambulatory Assessment ◽  
Survival Models ◽  
Qualitative And Quantitative ◽  
Fine Grained ◽  
The Mean

Loneliness is the feeling associated with a perceived lack of qualitative and quantitative aspects of social relationships. Loneliness is thus evidently intwined with individuals’ social behaviors in day-to-day life. Yet, little is known about the bidirectional pathways between loneliness and social interactions in daily life. In this study, we thus investigate (a) how loneliness predicts the frequency and duration of social interactions and (b) how frequency and duration of social interactions predict changes in loneliness. We examine these questions using fine-grained ambulatory-assessed sensor data of student’s social behavior covering 10 weeks (N_participants = 45, N_observations = 74,645). Before (T1) and after (T2) the ambulatory assessment phase, participants completed the UCLA loneliness scale, covering subscales on intimate, relational, and collective loneliness. Using multistate survival models, we show that T1 loneliness subscales are not significantly associated with differences in social interaction frequency and duration– only relational loneliness predicted shorter social interaction encounters. In predicting changes in loneliness subscales (T1-T2), only the mean duration of social interactions was negatively associated with collective loneliness. Thus, effects of loneliness on the structure of social interactions may be small or limited to specific forms of loneliness, implying that the quality of interactions may be more important.

scholarly journals Effect of morphological algorithms on medical imaging

2021 ◽  
Vol 8 (3) ◽  
pp. 1-8
Author(s):  
Cuong Phan Viet ◽  
Thao Ho Thi ◽  
Anh Le Tuan ◽  
Ha Nguyen Hong ◽  
Thanh Ha Quang
Keyword(s):  
Medical Imaging ◽  
Edge Detection ◽  
Medical Images ◽  
Computer Software ◽  
Diagnosis And Treatment ◽  
Detection Methods ◽  
Morphological Operators

Handling and improving the quality of medical images with the help of computer software is one of the important stages in the diagnosis and treatment. In this article, we focus on describing the new morphological algorithms by ITK (Insight Segmentation and Registration Toolkit). These morphological operators eliminate noise, detect good edges, and overcome the drawback of traditional edge detection methods.

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