Gotowe bibliografie tematyczne / GLOBALLY GUIDED FILTERING

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Gotowa bibliografia na temat „GLOBALLY GUIDED FILTERING”

Autor: Grafiati

Data publikacji: 11 września 2023

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Artykuły w czasopismach na temat "GLOBALLY GUIDED FILTERING"

Li, Zhengguo, i Jinghong Zheng. "Single Image De-Hazing Using Globally Guided Image Filtering". IEEE Transactions on Image Processing 27, nr 1 (styczeń 2018): 442–50. http://dx.doi.org/10.1109/tip.2017.2750418.

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Rathi, Sangeeta, i Savita Bamal. "DEEP LEARNING AND GLOBALLY GUIDED IMAGE FILTERING TECHNIQUE BASED IMAGE DEHAZING AND ENHANCEMENT". International Journal of Technical Research & Science Special, Issue3 (15.10.2020): 60–68. http://dx.doi.org/10.30780/specialissue-icaccg2020/043.

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Pareek, Anjali. "Deep Learning and Globally Guided Image Filtering Technique based Image Dehazing and Enhancement". International Journal for Research in Applied Science and Engineering Technology 8, nr 7 (31.07.2020): 1409–17. http://dx.doi.org/10.22214/ijraset.2020.30544.

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Rao, K. Srinivasa, S. Ramya, N. Ramyasri i M. Sirisha. "A Dehazing Benchmark with Real Hazy Outdoor Images". International Journal of Advance Research and Innovation 8, nr 2 (2020): 59–63. http://dx.doi.org/10.51976/ijari.822010.

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A single image dehazing is one of the problemin image processing. The main aim of using this method is to obtain certain transmission map to abolish hazes from a single input image. An optical model is evaluated and the basic transmission map under an additional filter is modified. For better conservation of haze image, the globally guided image filtering can be applied to produce sharper images and preserves details in regions of ﬁne structure visibly.

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Dai, Yaqiao, Renjiao Yi, Chenyang Zhu, Hongjun He i Kai Xu. "Multi-Resolution Monocular Depth Map Fusion by Self-Supervised Gradient-Based Composition". Proceedings of the AAAI Conference on Artificial Intelligence 37, nr 1 (26.06.2023): 488–96. http://dx.doi.org/10.1609/aaai.v37i1.25123.

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Monocular depth estimation is a challenging problem on which deep neural networks have demonstrated great potential. However, depth maps predicted by existing deep models usually lack fine-grained details due to convolution operations and down-samplings in networks. We find that increasing input resolution is helpful to preserve more local details while the estimation at low resolution is more accurate globally. Therefore, we propose a novel depth map fusion module to combine the advantages of estimations with multi-resolution inputs. Instead of merging the low- and high-resolution estimations equally, we adopt the core idea of Poisson fusion, trying to implant the gradient domain of high-resolution depth into the low-resolution depth. While classic Poisson fusion requires a fusion mask as supervision, we propose a self-supervised framework based on guided image filtering. We demonstrate that this gradient-based composition performs much better at noisy immunity, compared with the state-of-the-art depth map fusion method. Our lightweight depth fusion is one-shot and runs in real-time, making it 80X faster than a state-of-the-art depth fusion method. Quantitative evaluations demonstrate that the proposed method can be integrated into many fully convolutional monocular depth estimation backbones with a significant performance boost, leading to state-of-the-art results of detail enhancement on depth maps. Codes are released at https://github.com/yuinsky/gradient-based-depth-map-fusion.

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Fox, D., W. Burgard i S. Thrun. "Markov Localization for Mobile Robots in Dynamic Environments". Journal of Artificial Intelligence Research 11 (23.11.1999): 391–427. http://dx.doi.org/10.1613/jair.616.

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Localization, that is the estimation of a robot's location from sensor data, is a fundamental problem in mobile robotics. This papers presents a version of Markov localization which provides accurate position estimates and which is tailored towards dynamic environments. The key idea of Markov localization is to maintain a probability density over the space of all locations of a robot in its environment. Our approach represents this space metrically, using a fine-grained grid to approximate densities. It is able to globally localize the robot from scratch and to recover from localization failures. It is robust to approximate models of the environment (such as occupancy grid maps) and noisy sensors (such as ultrasound sensors). Our approach also includes a filtering technique which allows a mobile robot to reliably estimate its position even in densely populated environments in which crowds of people block the robot's sensors for extended periods of time. The method described here has been implemented and tested in several real-world applications of mobile robots, including the deployments of two mobile robots as interactive museum tour-guides.

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Hendricks-Sturrup, Rachele M., Kathleen M. Mazor, Amy C. Sturm i Christine Y. Lu. "Barriers and Facilitators to Genetic Testing for Familial Hypercholesterolemia in the United States: A Review". Journal of Personalized Medicine 9, nr 3 (1.07.2019): 32. http://dx.doi.org/10.3390/jpm9030032.

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Familial Hypercholesterolemia (FH) is an underdiagnosed condition in the United States (US) and globally, affecting an estimated 1/250 individuals. It is a genetic risk factor for premature cardiovascular disease and is responsible for an estimated 600,000 to 1.2 million preventable vascular events. Studies show that FH genetic testing can identify a causal gene variant in 60 to 80% of clinically suspected FH cases. However, FH genetic testing is currently underutilized in clinical settings in the US despite clinical recommendations and evidence supporting its use. Reasons for underutilization are not well understood. We conducted a literature review in the PubMed/MEDLINE database and eight peer-reviewed journals. After filtering for and reviewing 2340 articles against our inclusion criteria, we included nine commentaries or expert opinions and eight empirical studies reported between January 2014 and March 2019 in our review. After applying the Consolidated Framework for Implementation Research (CFIR), we identified a total of 26 potential barriers and 15 potential facilitators (estimated barrier to facilitator ratio of 1.73). We further estimated ratios of potential barriers to facilitators for each CFIR domain (Characteristics of Intervention, Outer Setting, Inner Setting, Characteristics of Individuals, and Process). Findings derived from our systematic approach to the literature and calculations of estimated baseline ratios of barriers and facilitators can guide future research to understand FH genetic testing implementation in diverse clinical settings. Our systematic approach to the CFIR could also be used as a model to understand or compare barriers and facilitators to other evidence-based genetic testing processes in health care settings in the US and abroad.

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Ning, Yu, Yong-Ping Jin, You-Duo Peng i Jian Yan. "Low-illumination underwater image enhancement based on non-uniform illumination correction and adaptive artifact elimination". Frontiers in Marine Science 10 (1.09.2023). http://dx.doi.org/10.3389/fmars.2023.1249351.

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High-quality underwater images are used to extract information for a variety of purposes, including habitat characterization, species monitoring, and behavioral analysis. However, due to the limitation of non-uniform illumination environment and equipment, these images often have the problem of local over- or underexposure due to non-uniform illumination. Conventional methods cannot fully correct for this, and the dark area artifacts generated in the process of enhancing a low-light image cannot be readily fixed. Therefore, we describe a low-illumination underwater image enhancement method based on non-uniform illumination correction and adaptive artifact elimination. First, to eliminate the influence of non-uniform illumination on underwater images, an illumination equalization algorithm based on non-linear guided filtering corrects the non-uniform bright and dark regions of underwater images, and the dark channel prior algorithm and contrast-limited adaptive histogram equalization algorithm are introduced to prevent excessive enhancement of images and generation of dark regions. Then, in order to adaptively eliminate the dark area artifacts generated during the enhancement process, an adaptive multi-scale Retinex color fidelity algorithm with color restore is proposed to improve the color of the image and adaptively eliminate the dark area artifacts of the image. Then, the gray world white balance algorithm is used to adjust the color distortion caused by the attenuation of light. Finally, a multi-scale Retinex model parameter estimation algorithm is proposed to obtain the illumination component and reflection component of the image, and then, the enhanced image is obtained according to the Retinex model. The results show that the proposed method is superior to other algorithms regarding contrast, color restoration, and comprehensive effect, and improves low-illumination image enhancement technology.

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Rozprawy doktorskie na temat "GLOBALLY GUIDED FILTERING"

BHAGYANIDHI. "HAZE REMOVAL AND DETAIL ENHANCEMNT ALGORITHM USING GLOBALLY GUIDED FILTERING". Thesis, 2018. http://dspace.dtu.ac.in:8080/jspui/handle/repository/16406.

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Nowadays, the utilization and demand of image filters is very high in various applications of the areas of computer vision and image processing. Many local edge preserving smoothing strategies including Guided Filter [2] and Weighted Guided Filter [3] have been proposed in the literature earlier. These have been applied for studying different applications such as detail enhancement, de-hazing, feathering and many more. But these techniques may fail to preserve fine structured regions. A new technique, i.e. globally guided filtering has been introduced for solving this issue. In this study, I utilized the functionality of globally guided filter [1] in the de-hazing application as well as for the detail enhancement of the images. We have proposed a model for detail enhancement using globally guided filtering by incorporating edge-based weighting in it. Initially, a model was designed which was based on decomposition algorithm for detail enhancement. Then, the results are obtained for both of the algorithm models and compared. Whereas this model is having some limitation including noise amplification in flat patch areas and halo artifacts on edges. Therefore, edge-based weighting is incorporated to resolve this issue.

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Książki na temat "GLOBALLY GUIDED FILTERING"

Guss-West, Clare. Attention and Focus in Dance. Human Kinetics, 2021. http://dx.doi.org/10.5040/9781718212718.

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The Western approach to dance is largely focused on control and mastery of technique, both of which are certainly necessary skills for improving performance. But mindful attention, despite its critical role in high performance, has gotten short shrift—until now. Attention and Focus in Dance, a how-to book rooted in the 20 years of attentional focus findings of researcher Gabriele Wulf, will help dancers unlock their power and stamina reserves, enabling efficient movement, heightening their sensory perception and releasing their dance potential. Author Clare Guss-West—a professional dancer, choreographer, teacher and holistic practitioner—presents a systematic, science-based approach to the mental work of dance. Her approach helps dancers hone the skills of attention, focus and self-cueing to replenish energy and enhance their physical and artistic performance. A Unique, Research-Based Approach Here is what Attention and Focus in Dance offers readers: • A unique approach, connecting the foundations of Eastern movement with Western movement forms • Research-based teaching practices in diverse contexts, including professional dance companies, private studios, and programmes for dancers with special needs or movement challenges • Testimonies and tips from international professional dancers and dance educators who use the book's approach in their training and teaching • A dance-centric focus that can be easily integrated into existing training and teaching practice, in rehearsal, or in rehabilitation contexts to provide immediate and long-term benefits Guss-West explores attentional focus techniques for dancers, teachers and dance health care practitioners, making practical connections between research, movement theory and day-to-day dance practice. “Many dancers are using excessive energy deployment and significant counterproductive effort, and that can lead to a global movement dysfunction, lack of stamina and an increased risk of injury,” says Guss-West. “Attentional focus training is the most relevant study that sport science and Eastern-movement practice can bring to dance.” Book Organisation The text is organised into two parts. Part I guides dancers in looking at the attentional challenges and information overload that many professional dancers suffer from. It outlines the need for a systematic attention and focus strategy, and it explains how scientific research on attentional focus relates to dance practice. This part also examines the ways in which Eastern-movement principles intersect with and complement scientific findings, and it examines how the Eastern and scientific concepts can breathe new life into basic dance elements such as posture, turnout and port de bras. Attention and focus techniques are included for replenishing energy and protecting against energy depletion and exhaustion. Part II presents attention and focus strategies for teaching, self-coaching and cueing. It addresses attentional focus cues for beginners and for more advanced dancers and professionals, and it places attentional focus in the broader context of holistic teaching strategies. Maximising Dance Potential “Whether cueing others or yourself, cueing for high performance is an art,” Guss-West says. “Readers will discover how to format cues and feedback to facilitate effective neuromuscular response and enhance dancer recall of information and accessibility while dancing.” Attention and Focus in Dance offers an abundance of research-backed concepts and inspirational ideas that can help dancers in their learning and performance. This book aids readers in filtering information and directing their focus for optimal physical effect. Ultimately, it guides dancers and teachers in being the best version of themselves and maximising their potential in dance.

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Części książek na temat "GLOBALLY GUIDED FILTERING"

"Online Filtering Policies Around the World". W Internet Censorship and Regulation Systems in Democracies, 1–28. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-5225-9973-9.ch001.

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In this chapter, the authors begin by providing definitions about the basic terms in use and then proceed with an introduction to the global phenomenon of internet regulation. Furthermore, the development of online censorship is being presented, and the need for internet regulation is being discussed, along with the role that internet users can actually play. Additionally, the chapter provides a brief history of internet regulation systems (IRSs) around the world, and the authors examine the technical aspects of accessing the internet today and in previous years. Moreover, the reasons that initiate internet regulation policies are being reviewed. Next, the authors present and compare two contradictory kinds of IRSs: open vs. silent IRSs. Last, the authors explain how existing IRSs can be used as a guide in an effort to design and present a blueprint for a fair IRS.

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Hanke, Henrik, i Alf Neumann. "Web Mining". W Encyclopedia of Internet Technologies and Applications, 684–89. IGI Global, 2008. http://dx.doi.org/10.4018/978-1-59140-993-9.ch096.

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The scale and scope of information on the Internet has been extended enormously over the past decade. The growth of more and more intelligent Web-based services and applications has resulted in an enormous growth of potentially useful data of both commercial and non-commercial interest. While this rise has brought a great amount of positive impact on global economic, social, and political development, it also implies an enormous flood of information into an increasingly complex information space. This is to be found on a vast variety of topics originating from a vast variety of sources, which range from private Web sites containing different kinds of information, to business-to-business B2B platforms. In most cases, these data are of an unsorted and unstructured kind, making efficient and target-oriented information retrieval very hard, if not nearly impossible. Coping with the challenge of a lack of transparency can be remedied by intelligent software agents, also referred to as softbots, which guide users through finding, sorting, and filtering this accruing data on the Internet like commonly used search engines.

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Streszczenia konferencji na temat "GLOBALLY GUIDED FILTERING"

Lim, Dong-Pan, Seo-Won Ji, Yoon-Jae Yeo i Sung-Jea Ko. "Phase Matching Guided Filtering". W 2018 IEEE 7th Global Conference on Consumer Electronics (GCCE). IEEE, 2018. http://dx.doi.org/10.1109/gcce.2018.8574679.

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Muchtar, Kahlil, Khairun Saddami, Akhyar Bintang, Tjeng Wawan Cenggoro, Bens Pardamean, Chih-Yang Lin i Tia Ernita. "Lightweight Pedestrian Detection through Guided Filtering and Deep Learning". W 2021 IEEE 10th Global Conference on Consumer Electronics (GCCE). IEEE, 2021. http://dx.doi.org/10.1109/gcce53005.2021.9622111.

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Xu, Jiachen, Jingyu Gong, Jie Zhou, Xin Tan, Yuan Xie i Lizhuang Ma. "SceneEncoder: Scene-Aware Semantic Segmentation of Point Clouds with A Learnable Scene Descriptor". W Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/84.

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Besides local features, global information plays an essential role in semantic segmentation, while recent works usually fail to explicitly extract the meaningful global information and make full use of it. In this paper, we propose a SceneEncoder module to impose a scene-aware guidance to enhance the effect of global information. The module predicts a scene descriptor, which learns to represent the categories of objects existing in the scene and directly guides the point-level semantic segmentation through filtering out categories not belonging to this scene. Additionally, to alleviate segmentation noise in local region, we design a region similarity loss to propagate distinguishing features to their own neighboring points with the same label, leading to the enhancement of the distinguishing ability of point-wise features. We integrate our methods into several prevailing networks and conduct extensive experiments on benchmark datasets ScanNet and ShapeNet. Results show that our methods greatly improve the performance of baselines and achieve state-of-the-art performance.

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Achicanoy M., Wilson O., i Carlos F. Rodriguez H. "Integration of GPS and Accelerometer Uncertainties to Improve the Estimation of the Pose of Autonomous Vehicles". W ASME 2010 International Mechanical Engineering Congress and Exposition. ASMEDC, 2010. http://dx.doi.org/10.1115/imece2010-40463.

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Uncertainty fusion techniques based on Kalman filtering are commonly used to provide a better estimation of the state of a system. A comparison between three different methods to combine the sensor information in order to improve the estimation of the pose of an autonomous vehicle is presented. Two sensors and their uncertainty models are used to measure the observables states of a process: a Global Positioning System (GPS) and an accelerometer. Given that GPS has low sampling rate and the uncertainty of the position, calculated by double integration from the accelerometer signal, increases with time, first a resetting of the estimator based on accelerometer by the GPS measurement is done. Next, a second method makes the fusion of both sensor uncertainties to calculate the estimation. Finally, a double estimation is done, one for each sensor, and a estimated state is calculated joining the individual estimations. These methods are explained by a case study of a guided bomb.

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Madushika, U. G. D., T. Ramachandra i D. Geekiyanage. "Economic performance of green walls: A systematic review". W 10th World Construction Symposium. Building Economics and Management Research Unit (BEMRU), University of Moratuwa, 2022. http://dx.doi.org/10.31705/wcs.2022.31.

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Green walls are becoming an interesting solution to address the potential issues due to loss of greenery in the urban built environment. Even though green walls offer numerous benefits, the application pace of this concept seems slow in many parts of the world including Sri Lanka, which could be primarily due to the perception that the construction of green walls may involve additional costs compared to conventional walls and due to lack of awareness of its performance. This has driven the recent researchers to investigate the economic performance of green walls. However, those studies are limited to given local contexts, thus, the knowledge is scattered. Therefore, this paper aims to explore the economic performance of green walls in the global context collectively using a systematic review towards understanding the differences. Filtering the search for the period of 2010 to 2022 offered 15 out of 103 research articles suitable for the analysis. The cost data extracted shows high variability related to different characteristics of green walls, building envelopes, and climatic conditions. According to the review, the maintenance stage accounts for the highest portion of the Life Cycle Cost (LCC) in any type of green wall. The direct green façade is the cheapest option with lowest LCC compared to the indirect and living wall types while the living wall is the expensive type due to presence of more components. The review further confirms that in most instances, the economic benefits of green walls; increase property value, façade longevity, tax incentives, and energy-saving tend to offset the cost of green walls. It is expected that this collective review outcome would better guide the decision-making process of green wall implementation in a given context.

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