Dynamic Image Sampling Research Articles

RETRACTED: Simulation of sports cooperative learning model based on computer hardware system and dynamic image sampling

The motivation behind this article is to introduce significant teaching methods of physical education, tactical games, learning, and real education co-learning. Organized learning uses a hypothetical structure and the link between physical education, tactical games, learning, and collaborative learning. Intensive learning as an alternative to physical education, tactical games, learning, and an educational program rather than a collaborative learning system, as an educator concentrated on directing the educational curriculum where support is considered. Promote learning and training of teachers, it is all-encompassing social progress, going to school is impossible to mix physical and intellectual learning outcomes understudies. Including an excessive focus on education and the learning process is dynamic detection of the rotation. Holding on to the instructions and learning the actual assumptions of clear assumptions, Sports Education (SE) Tactical Games (TG), and Cooperative Leruiiirlg (CL) now act like a three-fold bench focus as learn. Use SE, TG, and CL educational outcomes to focus on the promotion of climate learning to consider as an alternative to filling Thor's coach Lu. The educator is deliberately busy with learning to move on the duty bench, truly significant, mistakes.

RETRACTED: Development characteristics of economic regions based on opencl design and dynamic image sampling

The study provides an analysis of key concepts explored in the development of literature in economic areas. Start by explaining the reason for a regional economic approach to growth in the world economy's growing international context. Therefore, Open is very difficult to discuss, arguing for the favorable conditions for the development of rules, regulations and promotions related to economic and regional characteristics and there is an environment-specific mix of social relations that facilitates the dissemination and exploitation of knowledge in the study based on which is often translated. This proposed Dynamic Scatter Diffraction (DSD) system introduces an image recognition system based on Open acceleration, mainly used on the economic region's high-speed conveyor belt. Open is a programming language standard that enables programmers to express application to any kernel setting its calculation. Open Compiler has been given the open freedom to parallelize the execution of kernel events at all levels. After feature identification, products have an automatic design. In this way, some evidence is provided about the origin of spatial fluctuations as the dynamic image is linked to the translated processes of data development processes and innovative activities. This greatly enhances the speed of preprocessing (image grayscale) image, combined with acceleration in economic areas, without accelerating the acquisition of the LBP (layout) feature of the target image, and accelerates the recognition of the Economic Region feature, which is characterized in conjunction with the Open standard in the design, design and dynamic image model-based identification process.

RETRACTED: Government ecological governance management based on heterogeneous multi-processors and dynamic image sampling

With the advent of the governance economy era, traditional government governance models face enormous challenges. Governance management is the source of power to enter the era of the knowledge economy. This is a profound change that governments have needed to implement innovative government governance models, methods of social organization, and management. Governments in many countries are now adopting the construction of e-government as a strategy and response to demonstrate their priority development competitive advantage over the international competition and the challenges of the knowledge economy that spreads around the world. Therefore, the establishment of a new model of government governance has great theoretical and practical significance for impulse and government management innovation. The Dynamic Image Classification Algorithm (DICA) system is introduced in the implementation of the image processing technology and global disaster detection proposed here, and of this dynamic image classification algorithm (DICA) of the government, sector to extract more effectively. DICA is the most important task, or it is a strong shadow, proper access to the characteristics of the disaster area, and a false impact on the impact of the disaster, overcoming false alarms. It creates patches of post-disaster aerial image data from pre-tailoring and pre-adjustment training and satellite imagery. DICA training, all patches to government-managed data modified without delay or image data extraction. Two types of proposed systems are high-speed operation and accuracy (96.6%) and detection of earth disasters.

RETRACTED: Simulation of oil painting art design based on 5 G mobile network and dynamic image sampling

Color quantization is the first critical step in automatic generation of oil as the main research goals. Design and Application of oil which line of the display system, and constructing a set of oil-based platform must be adapted to the layout of the system rise before the mobile terminal device in response to the movement. Use MVC development framework. Front-end uses the latest technology HTMLS and Bootstrap framework, the system has an effective cross platform compatibility and provide useless consistent device experience. The system established control systems and content colleague role-based authority, assign the appropriate role of detailed character content, so the development of the business logic of the system more standardized. Finally, the feasibility of the system to test and demonstrate the development of the various functions and performance 5 G mobile network and a moving image is displayed in the sample line painting.

Development of Art and Culture Creative Industry Using FPGA and Dynamic Image Sampling

The TVPS146’s digital video processor is used for digital video processing and image output on digital signal processing (DSP) ports. The following is a summary of the field programmable gate array (FPGA) features and programming principles. FPGA is designed by the ping‐pong operation, including serial to parallel conversion design, pipeline operation, and data interface synchronization. A dance video screenshot analysis microsystem is composed of it and video dynamic image processing. Finally, according to the number of dance culture performance institutions based on the internet from 2014 to 2018, the development strategy of dance culture and creativity based on the internet is put forward. The results show that the image sharpness of the video screenshots processed by the system is improved, and the effect of enhanced processing is achieved compared to the unprocessed video screenshots. In addition, after the video screenshot processed by the system is compressed, some details are lost and the outline of the image is blurred. The combination of internet immediacy, mass, grassroots, and interactivity can accelerate the development of China’s dance culture and creative industry and provide an effective practical foundation for innovation in the development of art and culture.

WITHDRAWN: Online Marketing Customer Search Based on 5G Network and Dynamic Image Sampling

Online marketing customer search information collection using 5G Networks based application and image gathering. Customers need the fastest speed network of 5G; Fifth-generation mobile networks are predicted to redact a large leap, as it turns into the subsequent cellular broadband. Fast height down load 20 gigabits through second, the pace in conformity with particular function tasks, inclusive of long-range obviousness medical, automotive, networking, virtual reality, augmented reality, and a variety of features regarding the Internet. Increased capital assets in Online Marketing fields, affecting the average annual employment statistics, data import standard economic growth and technology. It is an example of innovative activities. Twenty gigabits per second, fast peak download speeds to accomplish specific tasks, such as long-range precision medical, automotive, networking. When people consider whether this is related to global mobile users' participation in the digital economy, it becomes a gateway to access the Internet only in smartphones, mobile phones, and other wireless devices specific groups. With the proliferation of global monitoring sensors, 5G is widely used to construct a smart city and smart home. 5G network plays an important role in the video stream.

RETRACTED: Dynamic image sampling and swimming motion image recognition in immersive virtual reality

Video Analysis Underwater Virtual Reality Correction, common in technical analysis, supports elite swimming coaches and athletes as a visual aid. The underwater visual environment and dynamic camera behavior can degrade the video, which is considered an undesirable challenge. The athlete's movement can also blur the field of vision and create a cavitation effect on the air bubbles. Detects problems with existing systems configured using multiple image processing algorithms. The Naive Bayes algorithm studied swimming motion analysis and applied a video of broadcast sports to recognize immersive virtual reality by swimming and proposed here. The process is more sensitive to noise than global motion recovery, 1) local motion is usually buried in a complex motion, 2) clutter containing multiple objects: local motion analysis is for two reasons. It's difficult. However, a useful method for local motion analysis is to understand significant human activity from image sequences. In this study, Naive Bayes uses third robust motion estimation and prominent colors to sample detected objects and extract swimming motion. Swimmer From the moving image based on the above view, the observed wave resistance is observed through the suspension camera. The recorder data is synchronized with the immersive virtual reality of evaluating the actual moving image to capture detailed swimming movements. Principal Component Analysis (PCA) is analyzed by time-frequency. These recorders' data are displayed in chronological order with a different swimming immersion virtual reality than the main frequency.

RETRACTED: Simulation of swimming sports image recognition based on multi-core processor and dynamic image sampling

Abstract Human understanding of human movement is one of the most important areas of research activities. In recent years, the use of RGB-D movement recognition data has raised concerns. With artificial intelligence development, the depth of learning technology has made great success in computer vision. A variety of application scenarios and real-time constraints computer vision applications spurred on computer architecture conducted extensive research. These studies take advantage of image processing algorithms and computer vision functions to maximize and improve efficiency through the hardware's scalability. Growth, programmable computing power, and multi-core architecture's potential to accelerate parallel image processing and computer vision algorithms provide a broad prospect. Conduct a new study to discover the unique attributes of three computer vision algorithms that are widely used and determine the optimal computing architecture for each algorithm. Advantages of parallel processing hardware to provide modern programmable graphics data and the thread of instructions, which is significantly faster than the standard CPU implementation.

RETRACTED: Valsartan treatment of congestive heart failure based on FPGA and dynamic image sampling

Abstract The diagnosis of coronary illness is the most troublesome errand in the clinical field. Computed Tomography (CT) is a significant imaging methodology used to analyze cardiovascular illness. Cardiovascular division from CT filters is essential for clinical understanding, significant data for quantitative examination of the heart and coronary corridor structure. This paper proposes a completely mechanized calculation for heart division dependent on an arbitrary walk model and programmed introductory seed recognition. Cardiovascular division from CT checks is essential for clinical understanding and basic data for quantitative examination of the heart and coronary conduit structure. The conventional system has some problems, like processing time is high and gives low accuracy, so the proposed Regressive Image Classification Technique (RICT) system is implemented. The proposed system RICT presents a fully automated algorithm for heart disease classification, based on the Regressive Image Classification Technique (RICT) and automated initial seed detection. It can outflank conventional systems dependent on a formalisation of on-chip memory design alternatives and a force model. Contrasted with business FPGA blend and High-Level Synthesis instruments, our outcomes show that the proposed calculations.

RETRACTED: Urban ecological forestry analysis based on FPGA and dynamic image sampling

Abstract Urban ecological forestry is one of the analyses leading to high global mortality. Urban ecological forestry is based on the destruction of forest habitats and the loss of biodiversity. It is the growth of animals and plants in the world. It is characterized by a single irregular urban forest all over the world. Therefore, it is necessary to detect the affected area according to the application, find out and deal with it early. It is generally believed that urban ecosystem forests are essential indicators of destruction. The previous method used Support Vector Machine (SVM) and Short Time Fourier Transform Algorithm (STFT) to reduce the accuracy and efficiency of C.T. (Computed Tomography) images. The image processing system based on urban ecological forest analysis and detection is being processed. The conversion method is prolonged, and it is impossible to verify the image using advanced risk architecture. The proposedProgrammable Gate Array) is used to develop image processing and easily interface data without complexity. Programmable Gate Array is mainly realized by ASIC (Application Specific Integrated Circuit). This system accelerates forest detection and loss detection and can be used as a single processing system or as a component of an image detection system. Image processing systems rely on double-sided filtering, edge detection, multiple thresholds, image segmentation, morphological image processing, and image labeling to solve urban ecological forestry analysis symptoms.

RETRACTED: Image recognition of dance moving based on heterogeneous multiprocessor and dynamic image sampling

Motion capture technology has made great strides in computer science and information technology. The design of dance movements requires simulation and dancing of design elements to be critical to overcome the obstacle; 3d aesthetics need to be optimized and cause body rotation problems. Using image analysis technology to establish a mathematical model based on dance motion capture technology, it takes the five main dance movement components as the primary research object. It then proposes the continuity similarity of dance movement. Incorporate composite data obtained from samples during alignment. The proposed system's high tracking accuracy system indicates that it is suitable for various dance training programs based on the game. Video application product video studio software, and programming program, multimedia design of dance movement in the computer, and then realize the effect of dance technology in conjunction with computer technology. Finally, it provides a symbolic reference to dance movement technology research and design.

Dynamic Image Sampling Using a Novel Variance Based Probability Mass Function

Incremental sampling can be applied in scientific imaging techniques whenever the measurements are taken incrementally, i.e., one pixel position is measured at a time. It can be used to reduce the measurement time as well as the dose impinging onto a specimen. For incremental sampling, the choice of the sampling pattern plays a major role in order to achieve a high reconstruction quality. Besides using static incremental sampling patterns, it is also possible to dynamically adapt the sampling pattern based on the already measured data. This is called dynamic sampling and allows for a higher reconstruction quality, as the inhomogeneity of the sampled image content can be taken into account. Several approaches for dynamic sampling have been published in the literature. However, they share the common drawback that homogeneous regions are sampled too late. This reduces the reconstruction quality as fine details can be missed. We overcome this drawback using a novel probabilistic approach to dynamic image sampling (PADIS). It is based on a data driven probability mass function which uses a local variance map. In our experiments, we evaluate the reconstruction quality for scanning electron microscopy images as well as for natural image content. For scanning electron microscopy images with a sampling density of 35% and frequency selective reconstruction, our approach achieves a PSNR gain of +0.92 dB compared to other dynamic sampling approaches and +1.42 dB compared to the best static patterns. For natural images, even higher gains are achieved. Experiments with additional measurement noise show that for our method the sampling patterns are more stable. Moreover, the runtime is faster than for the other methods.

A Framework for Dynamic Image Sampling Based on Supervised Learning

Sparse sampling schemes can broadly be classified into two main categories: static sampling where the sampling pattern is predetermined, and dynamic sampling where each new measurement location is selected based on information obtained from previous measurements. Dynamic sampling methods are particularly appropriate for pointwise imaging methods, in which pixels are measured sequentially in arbitrary order. Examples of pointwise imaging schemes include certain implementations of atomic force microscopy, electron back scatter diffraction, and synchrotron X-ray imaging. In these pointwise imaging applications, dynamic sparse sampling methods have the potential to dramatically reduce the number of measurements required to achieve a desired level of fidelity. However, the existing dynamic sampling methods tend to be computationally expensive and are, therefore, too slow for many practical applications. In this paper, we present a framework for dynamic sampling based on machine learning techniques, which we call a supervised learning approach for dynamic sampling (SLADS). In each step of SLADS, the objective is to find the pixel that maximizes the expected reduction in distortion (ERD) given previous measurements. SLADS is fast because we use a simple regression function to compute the ERD, and it is accurate because the regression function is trained using datasets that are representative of the specific application. In addition, we introduce an approximate method to terminate dynamic sampling at a desired level of distortion. We then extend our algorithm to incorporate multiple measurements at each step, which we call groupwise SLADS. Finally, we present results on computationally generated synthetic data and experimentally collected data to demonstrate a dramatic improvement over state-of-the-art static sampling methods