The proceedings contain 153 papers. The topics discussed include: transaction data management optimization based on multi-partitioning in blockchain systems;semi-asynchronous federated learning optimized for NON-IID d...
ISBN:
(纸本)9798350329223
The proceedings contain 153 papers. The topics discussed include: transaction data management optimization based on multi-partitioning in blockchain systems;semi-asynchronous federated learning optimized for NON-IID data communication based on tensor decomposition;HKTGNN: hierarchical knowledge transferable graph neural network-based supply chain risk assessment;DQR-TTS: semi-supervised text-to-speech synthesis with dynamic quantized representation;deep reinforcement learning-based network moving target defense in DPDK;iNUMAlloc: towards intelligent memory allocation for AI accelerators with NUMA;and predictive queue-based low latency congestion detection in data center networks.
The proceedings contain 117 papers. The topics discussed include: detection of a novel dual attack in named data networking;fair DMA scheduler for low-latency accelerator offloading;multi-attribute decision-making met...
ISBN:
(纸本)9781665464970
The proceedings contain 117 papers. The topics discussed include: detection of a novel dual attack in named data networking;fair DMA scheduler for low-latency accelerator offloading;multi-attribute decision-making method based on interval intuitionistic trapezoidal fuzzy number to determine the expert weight: note: sub-titles are not captured in Xplore and should not be used;binary-level directed symbolic execution through pattern learning;an efficient metric-based approach for static use-after-free detection;a graph convolution neural network based method for insider threat detection;maintenance worker scheduling for charging pile fault: a multi-agent RL approach;towards secure bilateral friend query with conjunctive policy matching in social networks;structure-noise-aware anchor link prediction across social networks;file system to support secure cloud-based sharing;discovering agent models using process mining: initial approach and a case study;and towards agent-based simulation of the parallel trading market of pharmaceuticals.
The proceedings contain 222 papers. The topics discussed include: DRL-deploy: adaptive service function chains deployment with deep reinforcement learning;accuracy vs. efficiency: achieving both through hardware-aware...
ISBN:
(纸本)9781665435741
The proceedings contain 222 papers. The topics discussed include: DRL-deploy: adaptive service function chains deployment with deep reinforcement learning;accuracy vs. efficiency: achieving both through hardware-aware quantization and reconfigurable architecture with mixed precision;cmss: collaborative modeling of safety and security requirements for network protocols;FGPA: fine-grained pipelined acceleration for depthwise separable CNN in resource constraint scenarios;Dyacon: JointCloud dynamic access control model of data security based on verifiable credentials;understanding the runtime overheads of deep learning inference on edge devices;and alleviating imbalance in synchronous distributed training of deep neural networks.
The proceedings contain 35 papers. The topics discussed include: research on a parallel algorithm for video image compression of transmission line inspection;implementation of differential compression algorithm for su...
ISBN:
(纸本)9798400709166
The proceedings contain 35 papers. The topics discussed include: research on a parallel algorithm for video image compression of transmission line inspection;implementation of differential compression algorithm for substation inspection video images based on wavelet transform;a key frame extraction method for intelligent patrol video of large-scale substation based on sequence segmentation;advantages of unmanned aerial vehicle multi-view images in intelligent matching and defect hidden danger detection of substation inspection;automatic quality correction algorithm design for transmission line images based on the saliency model;research on video image transmission system of power equipment inspection based on deep learning;and polarization image processing technology based on machine vision detection.
The proceedings contain 29 papers. The special focus in this conference is on Machine Learning, Image processing, Network Security and data Sciences. The topics include: The Potential of 1D-CNN for EEG Menta...
ISBN:
(纸本)9783031622168
The proceedings contain 29 papers. The special focus in this conference is on Machine Learning, Image processing, Network Security and data Sciences. The topics include: The Potential of 1D-CNN for EEG Mental Attention State Detection;marker-Based Augmented Reality Application in Education Domain;detection and Classification of Waste Materials Using Deep Learning Techniques;Deep Learning Based EV’s Charging Network Management;internet of Medical Things: Empowering Mobility and Health Monitoring with a Smart Walking Stick;SynText - data Augmentation Algorithm in NLP to Improve Performance of Emotion Classifiers;preface;Phishing Detection Using 1D-CNN and FF-CNN Models Based on URL of the Website;A Comparative Analysis of ML Based Approaches for Identifying AQI Level;a Review of Authentication Schemes in Internet of Things;advancements in Facial Expression Recognition: A Comprehensive Analysis of Techniques;a Deep Learning Method for Obfuscated Android Malware Detection;COVID-19 Detection from Chest X-Ray Images Using GBM with Comparative Analysis;hate Speech Detection Using Machine Learning and Deep Learning Techniques;effectiveness of Influencer Marketing on Gen Z Consumers;compressors Using Modified Sorting and Parallel Counting;violence Detection in Indoor Domestic Environment Using Multimodal Information;Code-Mixed Language Understanding Using BiLSTM-BERT Multi-attention Fusion Mechanism;diabetes Prediction Using Machine Learning Classifiers;crop Yield Prediction Using Machine Learning Approaches;Comparative Analysis of Economy-Based Multivariate Oil Price Prediction Using LSTM;MRI Based Spatio-Temporal Model for Alzheimer’s Disease Prediction;bridging the Gap: Condensing Knowledge Graphs for Metaphor processing by Visualizing Relationships in Figurative and Literal Expressions;a Novel Unsupervised Learning Approach for False data Injection Attack Detection in Smart Grid;a Multi-stage Encryption Technique Using Asymmetric and Various Symmetric Ciphers;speed-Invar
The proceedings contain 202 papers. The topics discussed include: multi-relational graph convolutional networks for skeleton-based action recognition;identifying the right person in social networks with double metapho...
ISBN:
(纸本)9781665414852
The proceedings contain 202 papers. The topics discussed include: multi-relational graph convolutional networks for skeleton-based action recognition;identifying the right person in social networks with double metaphone codes;a novel strong cache consistency mechanism in ICN based on role division and lease model;demystifying the largest live game streaming platform via black-box measurement;framework-agnostic optimization of repeated skewed joins at massive scale;remote procedure call optimization of big data systems based on data awareness;MCSEC: secure coded matrix multiplication scheme for edge computing with minimum communication cost;low-rate DoS attack detection based on WPD-EE algorithm;user identity linkage across location-based social networks with spatio-temporal check-in patterns;optimizing 3-D placement of multiple UAVs based on Taguchi’s method;and feature envy detection based on Bi-LSTM with self-attention mechanism.
As a novel bio-inspired imaging device, the spike camera shows remarkable potential in capturing ultra-highspeed motion scenes by simulating the mechanism of the retinal fovea. It achieves a temporal resolution of ten...
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ISBN:
(纸本)9798331529543;9798331529550
As a novel bio-inspired imaging device, the spike camera shows remarkable potential in capturing ultra-highspeed motion scenes by simulating the mechanism of the retinal fovea. It achieves a temporal resolution of tens of thousands of Hz through spike emission. However, this capability presents significant challenges in terms of large-scale data storage and transmission, along with stringent fidelity requirements for spike data, thus posing a formidable obstacle to the lossless compression of continuous spike streams. In this paper, we introduce an effective image representation method for spikes, along with an intensity remapping technique to mitigate noise effects in spike streams. Building on this, we propose a learned lossless spike datacompression model. To our knowledge, it is the first learning-based model for lossless spike stream compression. Experimental results demonstrate that our method can realize state-of-the-art performance for spike data lossless compression.
Emerging event cameras acquire visual information by detecting time domain brightness changes asynchronously at the pixel level and, unlike conventional cameras, are able to provide high temporal resolution, very high...
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ISBN:
(纸本)9798331529543;9798331529550
Emerging event cameras acquire visual information by detecting time domain brightness changes asynchronously at the pixel level and, unlike conventional cameras, are able to provide high temporal resolution, very high dynamic range, low latency, and low power consumption. Considering the huge amount of data involved, efficient compression solutions are very much needed. In this context, this paper presents a novel deep-learning-based lossless event datacompression scheme based on octree partitioning and a learned hyperprior model. The proposed method arranges the event stream as a 3D volume and employs an octree structure for adaptive partitioning. A deep neural network-based entropy model, using a hyperprior, is then applied. Experimental results demonstrate that the proposed method outperforms traditional lossless datacompression techniques in terms of compression ratio and bits per event.
In recent years, the proliferation of cloud services, particularly social media, has spurred research on encryption-then-compression (EtC) systems for secure and efficient multimedia transmission. EtC systems compress...
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ISBN:
(纸本)9798331529543;9798331529550
In recent years, the proliferation of cloud services, particularly social media, has spurred research on encryption-then-compression (EtC) systems for secure and efficient multimedia transmission. EtC systems compress encrypted images or provide compression-resilient encryption. To address the need for embedding authentication, copyright data, or tags to images in cloud services, this paper introduces a novel data hiding scheme for the EtC system. The EtC system which this paper focuses on converts an RGB color image to the YCbCr color image, followed by horizontally joining three color component images to form a grayscale image, and encrypts this grayscale image in non-overlapping blocks using block permutation, block rotation/inversion, and brightness inversion. The proposed data hiding scheme conceals data in unencrypted images and can extract it from encrypted images by manipulating diagonal pixel values within blocks. Sorting keys, generated from intra-block pixel value characteristics, ensure correct data sequence recovery. Moreover, the proposed scheme is reversible, allowing for the removal of embedded information, and uses different pixels within the same block for dual embeddings to increase payload. Compared to conventional schemes for the EtC system, the proposed scheme leverages all three visual encryption processes and considers the RGB-to-YCbCr conversion. Performance evaluation results confirm the effectiveness of the proposed scheme.
Massive MIMO using decentralized baseband processing (DBP) architecture has been envisioned as a promising technique to enable the functionality of future wireless systems due to its ability to reduce fronthaul cost a...
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ISBN:
(纸本)9798350304060;9798350304053
Massive MIMO using decentralized baseband processing (DBP) architecture has been envisioned as a promising technique to enable the functionality of future wireless systems due to its ability to reduce fronthaul cost and computational complexity. The precoding design under the DBP architecture has been studied recently, but most of the existing algorithms are encountered with excessive interconnection costs, or the algorithms are only tailored for the total power constraints. In view of this, we propose a communication-efficient linear compression-based precoding (LCP) scheme and study the multi-carrier joint compression and precoding design (MC-JCPD) problem under the practical per-antenna power constraints. Specifically, in the LCP scheme, the central unit compresses the transmit signals on subcarriers by individual compressors and then sends the low-dimensional compressed signals to the distributed units for precoding. However, the associated MC-JCPD problem is challenging to solve since the compressor and the precoders are complexly coupled. To address the problem, we propose two efficient algorithms based on the penalty dual decomposition-based method and the matrix factorization-based method. Simulation results show that the proposed LCP scheme can approach the centralized scheme but with a significantly reduced interconnection cost.
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