At present, parallel fuzzing mainly has the following two problems. The first is that parallelization is mainly aimed at single-machine with multi-core situation, and there is no test case generation method suitable f...
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HAYABUSA2 asteroid probe has completed its mission successfully in the vicinity of asteroid Ryugu on November 13, 2019. It is on its way to the Earth now. Digital Electronics and Optical Navigation Camera (DE-ONC) was...
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ISBN:
(纸本)9781510638112;9781510638105
HAYABUSA2 asteroid probe has completed its mission successfully in the vicinity of asteroid Ryugu on November 13, 2019. It is on its way to the Earth now. Digital Electronics and Optical Navigation Camera (DE-ONC) was developed for scientific observation and real-time image recognition for optical navigation. The development process and its high-speed wire rate signal processing architecture of onboard electronics are explained in this lecture. Highly efficient lossless and lossy image compression algorithm were developed to send observed images through within the limited capacity of communication channels between the asteroid Ryugu and the Earth for scientific purposes. Onboard sensitivity and distortion correction functions for image sensors were also developed to improve compression ratio of images. High level synthesis technology was employed to implement the image recognition functions for optical navigation functions into limited numbers of space grade field programmable gate arrays (FPGAs) and to achieve wire rate signal processing speed. It must also satisfy high reliability and safety requirements of HAYABUSA2 missions. Functional distribution mode, standby redundancy mode and hot redundancy mode were realized with the same device configuration. Model based design was performed to satisfy these requirements. The onboard imageprocessing unit of DE-ONC adopts a unified language processing system and a distributed memory model with reference to a parallel inference machine developed for the Fifth Generation Computer Systems aiming at artificial intelligence technology development. Its imageprocessing module integrates a radiation hardened micro-controller unit (MCU) and FPGAs with the unified language processing system and the distributed object model.
Massive amounts of data are generated by sensor networks, edge computers, IoT devices, and enterprise networks. To process this volume of data requires (1) a scalable programming model that is not only concurrent and ...
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Massive amounts of data are generated by sensor networks, edge computers, IoT devices, and enterprise networks. To process this volume of data requires (1) a scalable programming model that is not only concurrent and distributed, but supports the mobility of data and processes (actors), and (2) algorithms to distribute computations between nodes in a manner that improves overall performance while considering energy use in the system. With appropriate programming tools, we can distribute a given computation in a way that makes effective use of edge devices to improve performance while lowering energy consumption. The paper describes our work building on ideas based on the Actor model of computation. These include characterizing the relation of performance and energy consumption in parallel computation, and methods to support scalable placement mechanisms under dynamically changing network conditions and computational loads on edge devices. The paper will conclude with a presentation with a summary of open research problems.
The proceedings contain 130 papers. The special focus in this conference is on Intelligent Computing. The topics include: A Comparable Study on Dimensionality Reduction methods for Endmember Extraction;Hyperspectral I...
ISBN:
(纸本)9783030845315
The proceedings contain 130 papers. The special focus in this conference is on Intelligent Computing. The topics include: A Comparable Study on Dimensionality Reduction methods for Endmember Extraction;Hyperspectral image Classification with Locally Linear Embedding, 2D Spatial Filtering, and SVM;a Hierarchical Retrieval Method Based on Hash Table for Audio Fingerprinting;Automatic Extraction of Document Information Based on OCR and image Registration Technology;using Simplified Slime Mould Algorithm for Wireless Sensor Network Coverage Problem;super-Large Medical image Storage and Display Technology Based on Concentrated Points of Interest;person Re-identification Based on Hash;a Robust and Automatic Recognition Method of Pointer Instruments in Power System;partial Distillation of Deep Feature for Unsupervised image Anomaly Detection and Segmentation;an Evolutionary Neuron Model with Dendritic Computation for Classification and Prediction;Speech Recognition Method for Home Service Robots Based on CLSTM-HMM Hybrid Acoustic Model;serialized Local Feature Representation Learning for Infrared-Visible Person Re-identification;a Novel Decision Mechanism for image Edge Detection;Rapid Earthquake Assessment from Satellite imagery Using RPN and Yolo v3;attention-Based Deep Multi-scale Network for Plant Leaf Recognition;short Video Users’ Personal Privacy Leakage and Protection Measures;An Efficient Video Steganography Method Based on HEVC;analysis on the Application of Blockchain Technology in Ideological and Political Education in Universities;parallel Security Video Streaming in Cloud Server Environment;An Efficient Video Steganography Scheme for Data Protection in H.265/HEVC;an Improved Genetic Algorithm for distributed Job Shop Scheduling Problem;A Robust Lossless Steganography Method Based on H.264/AVC;detection of Pointing Position by Omnidirectional Camera.
The proceedings contain 130 papers. The special focus in this conference is on Intelligent Computing. The topics include: A Comparable Study on Dimensionality Reduction methods for Endmember Extraction;Hyperspectral I...
ISBN:
(纸本)9783030845285
The proceedings contain 130 papers. The special focus in this conference is on Intelligent Computing. The topics include: A Comparable Study on Dimensionality Reduction methods for Endmember Extraction;Hyperspectral image Classification with Locally Linear Embedding, 2D Spatial Filtering, and SVM;a Hierarchical Retrieval Method Based on Hash Table for Audio Fingerprinting;Automatic Extraction of Document Information Based on OCR and image Registration Technology;using Simplified Slime Mould Algorithm for Wireless Sensor Network Coverage Problem;super-Large Medical image Storage and Display Technology Based on Concentrated Points of Interest;person Re-identification Based on Hash;a Robust and Automatic Recognition Method of Pointer Instruments in Power System;partial Distillation of Deep Feature for Unsupervised image Anomaly Detection and Segmentation;an Evolutionary Neuron Model with Dendritic Computation for Classification and Prediction;Speech Recognition Method for Home Service Robots Based on CLSTM-HMM Hybrid Acoustic Model;serialized Local Feature Representation Learning for Infrared-Visible Person Re-identification;a Novel Decision Mechanism for image Edge Detection;Rapid Earthquake Assessment from Satellite imagery Using RPN and Yolo v3;attention-Based Deep Multi-scale Network for Plant Leaf Recognition;short Video Users’ Personal Privacy Leakage and Protection Measures;An Efficient Video Steganography Method Based on HEVC;analysis on the Application of Blockchain Technology in Ideological and Political Education in Universities;parallel Security Video Streaming in Cloud Server Environment;An Efficient Video Steganography Scheme for Data Protection in H.265/HEVC;an Improved Genetic Algorithm for distributed Job Shop Scheduling Problem;A Robust Lossless Steganography Method Based on H.264/AVC;detection of Pointing Position by Omnidirectional Camera.
The proceedings contain 130 papers. The special focus in this conference is on Intelligent Computing. The topics include: A Comparable Study on Dimensionality Reduction methods for Endmember Extraction;Hyperspectral I...
ISBN:
(纸本)9783030845216
The proceedings contain 130 papers. The special focus in this conference is on Intelligent Computing. The topics include: A Comparable Study on Dimensionality Reduction methods for Endmember Extraction;Hyperspectral image Classification with Locally Linear Embedding, 2D Spatial Filtering, and SVM;a Hierarchical Retrieval Method Based on Hash Table for Audio Fingerprinting;Automatic Extraction of Document Information Based on OCR and image Registration Technology;using Simplified Slime Mould Algorithm for Wireless Sensor Network Coverage Problem;super-Large Medical image Storage and Display Technology Based on Concentrated Points of Interest;person Re-identification Based on Hash;a Robust and Automatic Recognition Method of Pointer Instruments in Power System;partial Distillation of Deep Feature for Unsupervised image Anomaly Detection and Segmentation;an Evolutionary Neuron Model with Dendritic Computation for Classification and Prediction;Speech Recognition Method for Home Service Robots Based on CLSTM-HMM Hybrid Acoustic Model;serialized Local Feature Representation Learning for Infrared-Visible Person Re-identification;a Novel Decision Mechanism for image Edge Detection;Rapid Earthquake Assessment from Satellite imagery Using RPN and Yolo v3;attention-Based Deep Multi-scale Network for Plant Leaf Recognition;short Video Users’ Personal Privacy Leakage and Protection Measures;An Efficient Video Steganography Method Based on HEVC;analysis on the Application of Blockchain Technology in Ideological and Political Education in Universities;parallel Security Video Streaming in Cloud Server Environment;An Efficient Video Steganography Scheme for Data Protection in H.265/HEVC;an Improved Genetic Algorithm for distributed Job Shop Scheduling Problem;A Robust Lossless Steganography Method Based on H.264/AVC;detection of Pointing Position by Omnidirectional Camera.
Based on big data analysis technology, Hadoop and Spark big data parallel computing framework and HDFS distributed file storage database, we can complete the construction of political science research application plat...
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ISBN:
(纸本)9781665416672
Based on big data analysis technology, Hadoop and Spark big data parallel computing framework and HDFS distributed file storage database, we can complete the construction of political science research application platform. The political science research application platform pays attention to data capture, data cleaning, analysis and mining, visual display and other operations on the public comments and related responses of the masses under the government open platform and the opinions and contents published by netizens under the media social platform, which are involved in public opinion surveys under the current network environment, so as to complete the description and analysis of political phenomena with the help of the unique advantages of big data technology, and realize the innovation of political science research methods and the expansion of research fields. At the same time, it also makes an innovative attempt for the scientific and standardized research of political science.
imageprocessing arises as a promising domain for manifold applications requiring for heavy computing power and memory bandwidth with higher image resolution. Graphics processing unit (GPU) is widely used in image pro...
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imageprocessing arises as a promising domain for manifold applications requiring for heavy computing power and memory bandwidth with higher image resolution. Graphics processing unit (GPU) is widely used in imageprocessing algorithms but suffers from its powerful programmability that costs high hardware overhead. Moreover, GPU consumes much energy to access data from high-capacity register files, making it hard to implement on wearable devices. Enabling low power and efficient architecture with low hardware overhead remains *** this paper, we propose a programmable imageprocessing architecture (PIPArch) that explores the spatial locality in images to save energy while achieving high performance. We also design the instruction set architecture (ISA) to control the PIPArch. By supporting multiple parallel pipelines, we can keep the hardware utilization of PIPArch high. We evaluate the proposed PIPArch by developing the cycle-accurate simulator with some typical imageprocessing algorithms. Compared to NVIDIA Tesla V100 GPU, PIPArch gains 23.63x speedup.
Whole slide images (WSI) provide valuable phenotypic information for histological assessment and malignancy grading of tumors. The WSI-based grading promises to provide rapid diagnostic support and facilitate digital ...
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The modern synchrotron radiation facilities are producing massive diffraction images, which present a severe problem for data processing due to the high dimensionality of imaging data. Feature recognition and selectio...
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The modern synchrotron radiation facilities are producing massive diffraction images, which present a severe problem for data processing due to the high dimensionality of imaging data. Feature recognition and selection based deep learning methods have been developed to analyze data automatically. One crucial step is to use AI to screen out the diffraction images without Bragg spots. This paper proposes a feature distillation based approach for screening. It helps to reduce over 40% raw data volume and greatly alleviates the post processing workload faced by scientists.
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