The proceedings contain 149 papers. The topics discussed include: effects of AI on smart agriculture: a case study of digital agriculture base;image retrieval-based product identification for automatic checkout system...
ISBN:
(纸本)9781643684444
The proceedings contain 149 papers. The topics discussed include: effects of AI on smart agriculture: a case study of digital agriculture base;image retrieval-based product identification for automatic checkout systems;application of lightweight emotion recognition model in intelligent construction site monitoring;research on the application of smart wearable in the emotional management of the elderly;artificial intelligence technology in the field of broadcasting and hosting;intelligent inspection method for photovoltaic modules based on imageprocessing and deep learning;application of AI algorithms in power system load forecasting under the new situation;research on the intelligent operation and maintenance control system of power distribution network based on big data technology;research progress of intelligent rail transit train control system;and design and implementation of intelligent potted plant management system based on Internet of Things.
Homomorphic encryption (HE) allows secure computation on encrypted data without revealing the original data, providing significant benefits for privacy-sensitive applications. Many cloud computing applications (e.g., ...
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ISBN:
(纸本)9798400710797
Homomorphic encryption (HE) allows secure computation on encrypted data without revealing the original data, providing significant benefits for privacy-sensitive applications. Many cloud computing applications (e.g., DNA read mapping, biometric matching, web search) use exact string matching as a key operation. However, prior string matching algorithms that use homomorphic encryption are limited by high computational latency caused by the use of complex operations and data movement bottlenecks due to the large encrypted data size. In this work, we provide an efficient algorithm-hardware codesign to accelerate HE-based secure exact string matching. We propose CIPHERMATCH, which (i) reduces the increase in memory footprint after encryption using an optimized software-based data packing scheme, (ii) eliminates the use of costly homomorphic operations (e.g., multiplication and rotation), and (iii) reduces data movement by designing a new in-flash processing (IFP) architecture. CIPHERMATCH improves the software-based data packing scheme of an existing HE scheme and performs secure string matching using only homomorphic addition. This packing method reduces the memory footprint after encryption and improves the performance of the algorithm. To reduce the data movement overhead, we design an IFP architecture to accelerate homomorphic addition by leveraging the array-level and bit-level parallelism of NANDflash-based solid-state drives (SSDs). We demonstrate the benefits of CIPHERMATCH using two case studies: (1) Exact DNA string matching and (2) encrypted database search. Our pure software-based CIPHERMATCH implementation that uses our memory-efficient data packing scheme improves performance and reduces energy consumption by 42.9x and 17.6x, respectively, compared to the state-of-the-art software baseline. Integrating CIPHERMATCH with IFP improves performance and reduces energy consumption by 136.9x and 256.4x, respectively, compared to the software-based CIPHERMATCH impl
Data fusion, which involves integrating data from multiple sources, is increasingly valuable across various fields due to its ability to enhance information quality, accuracy, and reliability. This process enables a m...
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ISBN:
(纸本)9781510673816;9781510673809
Data fusion, which involves integrating data from multiple sources, is increasingly valuable across various fields due to its ability to enhance information quality, accuracy, and reliability. This process enables a more comprehensive understanding of complex phenomena by merging diverse datasets, providing insights that are otherwise unattainable. In the realm of remote sensing, where precise data acquisition is critical, fusion techniques have become indispensable, benefiting applications such as object detection, classification, and change detection. While much emphasis has been placed on spatial sharpening techniques in published studies, there remains a notable gap in establishing robust workflows for both lab-based and UAS-based remote sensing data fusion, particularly in the near-infrared (VNIR) and short-wave infrared (SWIR) regions. This study aims to investigate VNIR-SWIR fusion using data sourced from a medieval manuscript in a controlled laboratory environment and from UAS-based sensors in a real-world setting, addressing differences in system parameters and processing workflows. Despite challenges such as image registration issues, our analysis has yielded promising results, underscoring the importance of ongoing refinement in fusion methodologies to ensure comprehensive data interpretation and analysis across diverse datasets and environments.
During recent years, various hardware platforms were developed, each one suitable for use in different kind of applications. Platforms based on FPGAs, DSPs, GPUs, Single Board Computers, microcontrollers extend proces...
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ISBN:
(数字)9781665467179
ISBN:
(纸本)9781665467179
During recent years, various hardware platforms were developed, each one suitable for use in different kind of applications. Platforms based on FPGAs, DSPs, GPUs, Single Board Computers, microcontrollers extend processing capabilities and functionality in comparison with traditional personal computers based on a single CPU. Furthermore, co-design combines advantages from different types of processing units, rendering such architectures more attractive to researchers. In this paper, we achieve acceleration of imageprocessingalgorithms using a hardware platform based on a Raspberry Pi Single Board Computer and a custom designed FPGA HAT (Hardware Attached on Top) for RPi. The FPGA HAT consists of a Cyclone 10LP device The FPGA undertakes a computationally demanding load such as robotic vision algorithms exploiting parallelism, while the RPi can apply higher level operations such as running ROS (Robot Operating System). In order to overcome bottleneck in exchanging data between RPi and FPGA, a 16-bit parallel customized protocol was developed from scratch. The achieved transfer rate was about 50 Mbytes/sec when multi threaded software was implemented for the RPi. An image edge detector was implemented in order to verify the system performance. When only the RPi was used the processing rate was 48fps for images with resolution 512x512 pixels. RPi and FPGA co-design achieved processing rate 170fps for the same resolution images, which means an acceleration of about 350%. The proposed system was also evaluated in terms of power consumption.
Hair-related diseases are pervasive and can significantly impact individuals’ confidence and emotional well-being. Accurate diagnosis of these conditions poses challenges even for experienced professionals. However, ...
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This project aims to identify liver tumors using deep learning techniques. The core of our approach is a sophisticated neural network trained on real CT scans of patients with liver tumors. By leveraging advanced sign...
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The success and accuracy of analysis and processing of raster images of electronic assemblies entering the machine vision algorithms and models within the electronics manufacturing process depend on parameters of thes...
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Organelles are important structures and functional systems within cells, which are of great significance for understanding life phenomena and disease mechanisms. Therefore, the detection and segmentation of organelles...
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The proceedings contain 18 papers. The special focus in this conference is on Information Technologies and Intelligent Decision Making systems. The topics include: Comparative Analysis of Traditional Machine Learning ...
ISBN:
(纸本)9783031603174
The proceedings contain 18 papers. The special focus in this conference is on Information Technologies and Intelligent Decision Making systems. The topics include: Comparative Analysis of Traditional Machine Learning Approaches for Time Series Clustering Under Colored Noise;on the Open Transport Data Analysis Platform;investigation of the Characteristics of a Frequency Diversity Array Antenna;comparative Analysis of Fuzzy Controllers in a Truck Cruise Control System;implementation of a Blockchain-Based Software Tool to Verify the Authenticity of Paper Documents;development of Methods and algorithms for Dimension Reduction of Space Description for Pattern Recognition Problem;service for Checking Students’ Written Work Using a Neural Network;implementing a Jenkins Plugin to Visualize Continuous Integration Pipelines;elimination of Optical Distortions Arising from In Vivo Investigation of the Mouse Brain;quantum Fourier Transform in imageprocessing;choosing an Information Protection Mechanism Based on the Discrete Programming Method;application of Machine Learning Methods for Annotating Boundaries of Meshes of Perineuronal Nets;diagnostics of Animals Diseases Based on the Principles of Neutrosophic Sets and Sugeno Fuzzy Inference;the Technique of processing Non-Gaussian Data Based on Artificial Intelligence;development of Automation and Control System of Waste Gas Production Process Based on Information Technology;machine Learning and Data Mining.
In recent years, with the rapid development and popularization of artificial intelligence technology, CT has been more and more widely used in the field of clinical medicine as a non-volume micro body diagnostic metho...
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