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Ultra Sharp : Study of Single Image Super Resolution Using Residual Dense Network

Ultra Sharp : Study of Single Image Super Resolution Using R...

引用

computer Communication and Artificial Intelligence (CCAI), international conference on

作者： Karthick Prasad Gunasekaran Manning School of Information and Computer Sciences University of Massachusetts Amherst USA

For years, Single Image Super Resolution (SISR) has been an interesting and ill-posed problem in computer vision. The traditional super-resolution (SR) imaging approaches involve interpolation, reconstruction, and learning-based methods. Interpolation methods are fast and uncomplicated to compute, but they are not so accurate and reliable. Reconstruction-based methods are better compared with interpolation methods, but they are time-consuming and the quality degrades as the scaling increases. Even though learning-based methods like Markov random chains are far better than all the previous ones, they are unable to match the performance of deep learning models for SISR. This study examines the Residual Dense Networks architecture proposed by Yhang et al. and analyzes the importance of its components. By leveraging hierarchical features from original low-resolution (LR) images, this architecture achieves superior performance, with a network structure comprising four main blocks, including the residual dense block (rdB) as the core. Through investigations of each block and analyses using various loss metrics, the study evaluates the effectiveness of the architecture and compares it to other state-of-the-art models that differ in both architecture and components.

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computer vision-Based Speed Hump and Pothole Detection System for Vehicles

Computer Vision-Based Speed Hump and Pothole Detection Syste...

引用

Smart Systems for applications in Electrical Sciences (ICSSES), international conference on

作者： Harshalatha Y Ansh Singhal Aribenchi Suraj Jaya Chandak Aryan Kumar Department of ECE Siddaganga Institute of Technology Tumakuru India Department of ECE Siddaganga Institute of Technology Tumakuru

ISBN: (数字)9798331507671

ISBN: (纸本)9798331507688

In modern urban and rural road infrastructure, the detection and monitoring of road anomalies such as speed humps and potholes play a crucial role in ensuring road safety and infrastructure maintenance. Speed humps are raised pavement structures designed to slow down vehicles at specific locations, while potholes are depressions or holes in the road surface that can pose hazards to vehicles and pedestrians alike. Detecting these anomalies accurately and efficiently is essential to mitigate associated risks and ensure timely maintenance. computer vision-based methods use high-resolution cameras and machine learning algorithms to automatically detect and classify road anomalies with greater accuracy and efficiency. This approach enables early detection, real-time monitoring and timely maintenance thus improving road safety. In this paper, a real time implementation of pothole and hump detection system is proposed. The Deep Learning algorithm, YOLOv8 model is used to detect potholes and humps.

关键词： Accuracy Machine learning algorithms Pedestrians Software algorithms Cameras Smart systems Real-time systems Road safety Software Maintenance

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Application Research of computer Artificial Intelligence Technology in Intelligent Home System

Application Research of Computer Artificial Intelligence Tec...

引用

Data Science and computer Application (ICDSCA), IEEE international conference on

作者： Shuiying He Shanghai Institute of Commerce & Foreign Languages Shanghai China

This paper constructs an intelligent home monitoring system based on NI wireless sensor network. The system consists of multiple sensors to collect temperature and humidity, smoke, theft and other environmental data. The NI wireless sensor network node sends the data to the upper PC in the way of wireless network. LabVIEW software is used to judge and control the data on PC. The system has obtained a good man-machine interface. Among them, the software design process of the system is introduced in detail. The intelligent home monitoring system has the characteristics of NI wireless sensor network -- low power consumption, good real-time performance, easy to expand, remote monitoring and so on.

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A Provably Correct Floating-Point Implementation of Well Clear Avionics Concepts 23

A Provably Correct Floating-Point Implementation of Well Cle...

引用

23rd international conference on Formal Methods in computer-Aided Design, FMCAD 2023

作者： Ferreira, Nikson Bernardes Fernandes Moscato, Mariano M. Titolo, Laura Ayala-Rincon, Mauricio University of Brasilia Department of Computer Science Brasilia Brazil Analytical Mechanics Associates Hampton United States University of Brasilia Department of Mathematics Brasilia Brazil

ISBN: (纸本)9783854480600

The NASA DAIDALUS library provides formal definitions for Detect-and-Avoid avionics concepts such as when an aircraft is well-clear with respect to the surrounding air traffic, i.e., it does not operate in such proximity to create a collision hazard. While several properties are proven correct for DAIDALUS assuming ideal real number arithmetic, an actual implementation that uses floating-point numbers may behave unexpectedly because of round-off errors and run-time exceptions. This paper presents an experience report on the application of a formal methods toolchain to extract and verify floating-point C code from a real-valued specification of the well-clear module of DAIDALUS. This toolchain comprises the PVS theorem prover, the PRECiSA floating-point analyzer and code generator, and the Frama-C analysis suite. The generated code is automatically instrumented to detect when the control flow of the floating-point program may diverge from the ideal real number specification, and it is annotated with contracts that state the maximum accumulated round-off error. The absence of overflows is also formally verified for the generated code. In order to apply the toolchain to an industrial case study such as DAIDALUS, a formally verified pre-processing of the input specification is performed, which includes a program slicing and several semantic-preserving simplifications. © 2023 FMCAD Association and individual authors.

关键词： Semantics

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Realization of Combinational Circuits Using A Proposed Reversible Gate 3

Realization of Combinational Circuits Using A Proposed Rever...

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3rd international conference on Advances in Computing, Communication control and Networking, ICAC3N 2021

作者： Karmakar, Gobinda Bhattacharya, Arijit Biswas, Saroj Kr. Mandal, Ardhendu Das, Akhil Kumar Alam, Ekram Saha, Debasmita Charan Chowdhuri, Shib Acharya Prafulla Chandra College Dept. of Computer Science West Bengal India Gour Mahavidyalaya Dept. of Computer Science West Bengal India NIT Dept. of Computer Science Engineering Assam Silchar India University of North Bengal Dept. of Computer Science Applications West Bengal India University of Gour Banga Dept. of Computer Science West Bengal India

ISBN: (纸本)9781665438117

Because of the tremendous importance of very low power consumption, reversible logic synthesis came out as a significant method in circuit design. It is one of several design strategies available for creating digital logic circuits. Here we have presented a reversible gate which, the 'HAS' gate, that can function as a Universal circuit. The suggested gate can carry out fundamental operations such as AND, OR, NOT, NAND, NOR, XOR, and so on. It also can be used to perform the complex functionalities of adder, subtractor, decoder, multiplexer, magnitude comparator etc. The proposed design efficiently implements all the basic functionalities of all combinational circuits with ease. © 2021 IEEE.

关键词： computer circuits

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Design and Simulation Implementation of All-DC Offshore Wind Power System 3

Design and Simulation Implementation of All-DC Offshore Wind...

引用

3rd international conference on Clean and Green Energy Engineering, CGEE 2022

作者： Zhang, Boxuan College of Computer & Information Science Southwest University Chongqing China

ISBN: (数字)9781665452656

ISBN: (纸本)9781665452656

With the continuous advancement of the goal of 'carbon neutrality' and 'carbon peaking', renewable energy sources such as solar energy, wind energy, and hydropower have developed rapidly. Compared with onshore wind power, offshore wind power has natural advantages such as abundant wind energy resources and no land occupation. However, due to the charging current of submarine cables, the traditional AC transmission method is only suitable for short-distance, small-capacity offshore wind farms. For this reason, full DC offshore wind power technology came into being. This paper analyzes and studies the principle of the high-voltage direct current transmission system of the offshore wind farm. In the full direct current offshore wind power system designed in this paper, the low-voltage alternating current generated by the wind turbine is converted into low-voltage direct current through a diode rectifier bridge and further passed through the isolated DC-DC converter, the low-voltage direct current is converted into high-voltage direct current and be transmitted using submarine cables. To effectively adjust the voltage of the DC transmission system, we use a proportional-integral controller to close-loop control the phase shift angle of the DC-DC converter. Next, the high-voltage DC power is converted into a civil AC power distribution system by the onshore inverter, and the output AC power is adjusted in real-time by the integral controller. Finally, the correctness and effectiveness of the proposed control method are verified by building the corresponding simulation model in Matlab/Simulink. © 2022 IEEE.

关键词： DC-DC converters

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Apple Grade Classification Based on Convolutional Neural Network and Machine Learning 3

Apple Grade Classification Based on Convolutional Neural Net...

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3rd international conference on Neuromorphic Computing, ICNC 2024

作者： Yi, Lisong Zhong, Jing School of Computer Science and Engineering Chongqing Three Gorges University Chongqing China

ISBN: (纸本)9798331508661

The classification of apple grades is crucial for apple sales. Using computer vision technology as a non-destructive method to classify fruits has the advantages of high speed, applicability and high precision. This study focuses on the classification of apple grades using convolutional neural networks (CNN) and machine learning (ML) models. Firstly, the transfer learning method is adopted, and six popular CNN architectures (VGG-16, VGG-19, ResNet-50, MobileNet, EfficientNet, and Inception_V3) are used to compare the effects of different convolutional neural network models in processing apple classification. The results show that EfficientNet has the highest classification accuracy. Secondly, combining CNN and ML model, using EfficientNet to extract depth features and training ML models: K nearest neighbor (KNN), random forest classifier (RFC) and support vector machine (SVM) respectively. The results show that the classification accuracy is improved. Finally, the ensemble learning method is used to integrate multiple CNN_ML models through voting mechanism, and the final classification model is obtained, with an accuracy rate of 98.21%. According to the experimental results, this study was successful in apple grade classification and provided new ideas for apple grade classification. © 2024 IEEE.

关键词： Convolutional neural networks

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An Improved Method of CRIMINISI Algorithm 3

An Improved Method of CRIMINISI Algorithm

引用

2021年第三届先进计算机技术、信息科学与通信国际会议(CTISC2021)

作者： Yang Tao Zhao Junhong South China University of Technology school of Automation Science and Engineering

ISBN: (纸本)9781665418683

Nowadays, the research on image inpainting technology is a research topic of great significance in computer vision and graphics. As for the missing part of the image, humans can only analyze the remaining areas based on their own visual senses and experience, and then fill in the remaining missing areas because they do not know the original appearance of the image. In general, image restoration is a technology based on human vision and experience. In 2003, Criminisi et al. proposed a patching algorithm based on sample blocks. The algorithm gives priority to pixels based on the confidence level and adopts the best matching module method. This article provides a method to improve its confidence, changing its factor multiplication to linear addition and adding an additional judgment factor, which improves the effect of the inpainting.

关键词： Visualization Information science computer vision Maintenance engineering Image restoration Complexity theory

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Research on Scientific Recovery Training after Sports Injury with computer Assistance

Research on Scientific Recovery Training after Sports Injury...

引用

Data Science and computer Application (ICDSCA), IEEE international conference on

作者： Yongbing Chen Jing Hu West Yunnan University of Applied Sciences Dali China

In this paper, a virtual rehabilitation system for motor injury and control function of hands and upper limbs in patients with nerve injury was designed. The system collects human limb motion parameters through Kinect to drive the corresponding changes in the virtual scene. After collecting the three-dimensional coordinates of the junction nodes, Kinect represents each pair of adjacent junction nodes in the form of vectors, and takes the time series of vector changes instead of the motion trajectory as the evaluation object. The dynamic configuration of the training scene is realized by analyzing the XML file and establishing the personalized virtual scene. Finally, the data during the movement of the prototype is measured. The simulation results are compared with the experimental data to verify the feasibility of the design scheme.

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Automatic 3D Teeth Semantic Segmentation with Mesh Augmentation Network 3

Automatic 3D Teeth Semantic Segmentation with Mesh Augmentat...

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3rd international conference on Pattern Recognition and Machine Learning, PRML 2022

作者： Zhao, Qijun Wu, Xiao Zhu, Feiyu Liu, Jun Wei, Mingying Peng, Jiahan Lu, Yin Sichuan University College of Computer Science Chengdu China Sichuan University National Key Laboratory of Fundamental Science on Synthetic Vision Chengdu China Sichuan University State Key Laboratory of Oral Diseases National Clinical Research Center for Oral Diseases Department of Orthodontics West China Hospital of Stomatology Chengdu China The People's Hospital of Neijiang Department of Stomatology Neijiang China

ISBN: (数字)9781665499507

ISBN: (纸本)9781665499507

In this paper, we propose an approach that improves segmentation networks with automatic augmentation networks for dental mesh data. Since conventional data augmentation is to augment all samples uniformly with predefined parameters, it ignores the unique characteristics of a single tooth sample and cannot make good use of the data set. And the traditional method separates data augmentation and segmentation network training, so the augmented data cannot be well adapted to the network to make it play a good role. We adopt a joint optimization strategy to integrate the augmentation network and the segmentation network, so that the augmented tooth data is the most suitable for the segmentation network. In addition, we design new improved loss functions suitable for augmentation and segmentation networks. Experiments have shown that the automatic augmentation network in our proposed method, named MeshAugNet, can effectively improve the segmentation accuracy after it is used for tooth segmentation. In general, this work achieves a combination of 3D dental data auto- augmentation network and segmentation network, which improves the accuracy of tooth segmentation, and can be used to solve the problem of too few samples in tooth datasets. © 2022 IEEE.

关键词： Semantic Segmentation

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