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检索条件"任意字段=International Conference on Signal and Data Processing, ICSDP 2019"

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international conference on signal and data processing, icsdp 2019

International Conference on Signal and Data Processing, ICSD...

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international conference on signal and data processing, icsdp 2019

ISBN: (纸本)9789811583902

The proceedings contain 48 papers. The special focus in this conference is on signal and data processing. The topics include: Analysis of Accuracy of Supervised Machine Learning Algorithms in Detecting Denial of Service Attacks;An Improved Carrier Frequency Offset Estimation Under Narrowband Interference in OFDM Cognitive Radio;shot Boundary Detection Using Artificial Neural Network;digital Image Watermarking by Fusion of Wavelet and Curvelet Transform;machine Learning Feature Selection in Archery Performance;skin Lesion Classification Using Deep Learning;vehicle-to-Vehicle Driver Safety-Related data Transmission and Reception Using Li-Fi Technology;A Novel Approach for CBIR Using Four-Layered Learning;design of a Power Efficient Multiband Patch Antenna;brain Activity Analysis for Stress Recognition;deep Learning-Based Paperless Attendance Monitoring System;image Analytics to Detect Cigarette in an Image Using Deep Learning;custard Apple Leaf Parameter Analysis, Leaf Diseases, and Nutritional Deficiencies Detection Using Machine Learning;Discontinuous PWM Techniques to Eliminate Over-Charging Effects in Four-Level Five-Phase Induction Machine Drives;state of Charge Estimation Using Extended Kalman Filter;Frequency and Pattern Reconfigurable Antenna for WLAN and WiMAX Application;Implementation and Analysis of Low Power Consumption Full Swing GDI Full Adders;preface;deep Semantic Segmentation for Self-driving Cars;single Image Rain Removal Using Convolutional Neural Network;ring Oscillator-Based Physical Unclonable Functions;a Robust Approach of Estimating Voice Disorder Due to Thyroid Disease;smart Glasses: Digital Assistance in Industry;implementation of Hand Gesture Recognition System to Aid Deaf-Dumb People;Robust Underwater Animal Detection Adopting CNN with LSTM;face Recognition Using Golden Ratio for Door Access Control System.

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2nd international conference on signal and data processing, icsdp 2022

2nd International Conference on Signal and Data Processing, ...

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2nd international conference on signal and data processing, icsdp 2022

ISBN: (纸本)9789819914098

The proceedings contain 48 papers. The special focus in this conference is on signal and data processing. The topics include: Process Mining-Based Behavioral Modeling of Learners in Self-paced Learning Environment;blockchain Scalability: Solutions, Challenges and Future Possibilities;Solution of Unit Commitment Problems in GAMS Computational Environment;taxonomy and Implications of Machine Learning for Internet of Things: Qualities, Uses and Algorithms;auto Organizer: A Machine Learning-Based Tool for Automatic Organization of Files;twitter Spam Detection Using Different Machine Learning Techniques;on the Role of Perceptual Information in Image Classification;bengali Text Classification Based on Probability Measure;comprehensive Analysis on the Performance of Antenna Design Using Machine Learning Techniques;design and Analysis of Novel Miniaturized Metamaterial Structures for Multiband Applications;hybrid Particle Swarm Optimization Based Deep Learning Model for the Stage Classification of Lung Cancer;Interference Cancellation by Using Viterbi Algorithm for Space Base AIS System;a Stacked Multichannel Feature Map Based U-Net Model for Brain Tumor Segmentation;spatial Attention Gated U-Net Structure for Capsule Endoscopy Image Super-Resolution;feature Engineering and Selection for the Identification of Fake News in Social Media;early Detection of Pathological Myopia in Fundus Images Using Deep Learning;an Investigation on the Extractive Summarization of Kannada Text;rice Plant Leaf Disease Detection—A Comparison of Various Methodologies;combating Fake News with Machine Learning and Deep Learning Methods;Employing Soft Computing-Based GGA-MLP for Hyperparameter Optimization in COVID-19-Infected Lung Image data Classification;Design of Compact UWB MIMO Antenna with High Isolation Using Square Swirl Shape EBG Structure;forecasting with Fuzzy Time Series and Variation.

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3rd international conference on signal & data processing, icsdp 2023

3rd International Conference on Signal & Data Processing, IC...

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3rd international conference on signal and data processing, icsdp 2023

ISBN: (纸本)9789819795772

The proceedings contain 51 papers. The special focus in this conference is on signal and data processing. The topics include: Toward Feature Preserving High-Resolution Virtual Try-On;Single-Qubit Quantum Teleportation Using Three-Qubit Greenberger–Horne–Zeilinger (GHZ) State as Entanglement Resource and Basis for Quantum Measurement;performance Analysis of Optical Networks Using Deep Reinforcement Learning;design of Intelligent Solar Cooling System with IoT Monitoring;Analytical Review of 5G NR Channel Coding Techniques LDPC and Polar Codes;exploring Deep Learning Models for Classifying Wind Profiler Doppler Power Spectrum Contaminated by Ground Clutter;Harmonic Minimization in a Three-Phase Network Using the SSA Algorithm and Instantaneous PQ Theory;Efficient Rice Yield Classification: Accelerating ANN processing on PYNQ-Z2 Processor;An Area Efficient And Improvised Fault-Tolerant FIR Filter Using Word Voter;FPGA-Based Implementation of Cuffless Blood Pressure Measurement Using Photoplethysmogram signal;the Influence of Hybrid Algorithm in Manet for Estimating the Capacity of Quality of Service;classification of Currencies as Authentic or Counterfeit: A data-Driven Approach;sentiment Analysis in Image Caption Generation;implementation of Hybrid Machine Learning Algorithms in Classification of Real and Fake Profiles;image Extraction for Linear Segment in 3D Space;Suppression of Electromagnetic Emission in Electric Vehicle for EMC;Generating F1-Score to Predict Parkinson Disease with CNN Algorithm;Security and Privacy Analysis of Internet of Medical Things (IoMT) Based Smart Care Homes;machine Learning Model Based on Deep Neural Networks for Emotion Detection Using Audio-Visual Modalities;enhancing the Leaf Disease Detection Through Convolutional Neural Network;a Computational Analysis of Climate Change Sentiment on Social Media;gaussian Processes for Automating Model Selection.

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ICSIDP 2019 - IEEE international conference on signal, Information and data processing 2019

ICSIDP 2019 - IEEE International Conference on Signal, Infor...

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2019 IEEE international conference on signal, Information and data processing, ICSIDP 2019

ISBN: (纸本)9781728123455

The proceedings contain 635 papers. The topics discussed include: analysis of grating spectrum by using MUSIC for sub-arrays;ultrasonic inspection of prefabricated constructions using reverse time migration imaging method;variable velocity ambiguity numbers compensation method for near space target detection;accurate DOA estimation based on real-valued singular value decomposition;wideband DOA estimation under clutter using MIMO radar with sparse array;the influence of parameter selection for Renyi phase permutation entropy on abnormal change detection;a method of sound field control using beam deflection;hyperspectral inversion for soil moisture and temperature based on Gaussian process regression;interaction recognition using depth information based on 3D CNNs;robust minimum geometric power distortionless response beamforming with sparse constraint in heavy-tailed noise of unknown statistics;and research on the optimization strategy of phased array radar multi-area search performance.

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2019 4th international conference on Intelligent Computing and signal processing, ICSP 2019 - Algorithm and data Mining

2019 4th International Conference on Intelligent Computing a...

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2019 4th international conference on Intelligent Computing and signal processing, ICSP 2019

The proceedings contain 409 papers. The topics discussed include: case reasoning based design system for product packaging;research on X-ray welding image defect detection based on convolution neural network;radar imaging based on orthogonal matching pursuit via sparse constraint;global salient object detection based on multiple visual features;improved non-local means algorithm for image denosing;using FFT to reduce the computational complexity of sub-nyquist sampling based wideband spectrum sensing;design of intelligent MAN architecture based on MPLS-VPN;encryption cipher text retrieval scheme based on fully homomorphic encryption enterprise cloud storage;protein secondary structure online server predictive evaluation;and research and design of lightweight workflow engine based on SCA.

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COMPOSITE FEDERATED LEARNING WITH HETEROGENEOUS data 49

COMPOSITE FEDERATED LEARNING WITH HETEROGENEOUS DATA

引用

49th IEEE international conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Zhang, Jiaojiao Hu, Jiang Johansson, Mikael KTH Royal Inst Technol Sch Elect Engn & Comp Sci SE-10044 Stockholm Sweden Harvard Univ Massachusetts Gen Hosp Boston MA 02114 USA Harvard Univ Harvard Med Sch Boston MA 02114 USA

ISBN: (纸本)9798350344868;9798350344851

We propose a novel algorithm for solving the composite Federated Learning (FL) problem. This algorithm manages non-smooth regularization by strategically decoupling the proximal operator and communication, and addresses client drift without any assumptions about data similarity. Moreover, each worker uses local updates to reduce the communication frequency with the server and transmits only a d-dimensional vector per communication round. We prove that our algorithm converges linearly to a neighborhood of the optimal solution and demonstrate the superiority of our algorithm over state-of-the-art methods in numerical experiments.

关键词： Composite federated learning heterogeneous data local update

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EXTENSION OF CLIFFORD data REGRESSION METHODS FOR QUANTUM ERROR MITIGATION 49

EXTENSION OF CLIFFORD DATA REGRESSION METHODS FOR QUANTUM ER...

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49th IEEE international conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Perez-Guijarro, Jordi Pages-Zamora, Alba Fonollosa, Javier R. Univ Politecn Cataluna SPCOM Grp Barcelona Spain

ISBN: (纸本)9798350344868;9798350344851

In addressing the challenge posed by noise in actual quantum devices, the application of quantum error mitigation techniques becomes essential. These techniques are resource-efficient, making them viable for implementation in noisy intermediate-scale quantum devices, unlike the resource-intensive quantum error correction codes. A prominent example among these techniques is Clifford data Regression, which employs a supervised learning approach. This work explores two variants of this technique, both of which add a non-trivial set of gates to the original circuit. The first variant leverages copies of the original circuit, whereas the second approach adds a layer of 1-qubit rotations.

关键词： Quantum Error Mitigation Clifford data Regression Supervised Learning

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GENERALIZED SPECAUGMENT VIA MULTI-RECTANGLE INVERSE MASKING FOR ACOUSTIC SCENE CLASSIFICATION 49

GENERALIZED SPECAUGMENT VIA MULTI-RECTANGLE INVERSE MASKING ...

引用

49th IEEE international conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Byun, Pil Moo Chang, Joon-Hyuk Hanyang Univ Dept Artificial Intelligence Seoul South Korea Hanyang Univ Dept Elect Engn Seoul South Korea

ISBN: (纸本)9798350344868;9798350344851

In this paper, we present the multi-rectangle inverse masking (MRIM), an extension and generalization of the traditional SpecAugment technique, for acoustic scene classification. While SpecAugment, observed from its unmasked areas, primarily forms rectangles around the input corners, our novel strategy generates rectangles at random positions with varied sizes, enhancing the data augmentation capacity. Our evaluations, conducted on the DCASE 2019 and 2020 datasets using CNN architectures like ResNet50 and BC-Res2Net, highlighted notable performance enhancements. Importantly, our method demonstrated resilience even when post-processing masking is applied to unseen test data, emphasizing its robustness across diverse acoustic scenes. To gain a deeper understanding of our method's impact, we utilize the grad-CAM++ technique, a tool from explainable AI, to explore how masking influences model activations.

关键词： acoustic scene classification data augmentation SpecAugment multi-rectangle inverse masking grad-CAM plus

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CAN LARGE-SCALE VOCODED SPOOFED data IMPROVE SPEECH SPOOFING COUNTERMEASURE WITH A SELF-SUPERVISED FRONT END? 49

CAN LARGE-SCALE VOCODED SPOOFED DATA IMPROVE SPEECH SPOOFING...

引用

49th IEEE international conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Wang, Xin Yamagishi, Junichi Natl Inst Informat Tokyo Japan

ISBN: (纸本)9798350344868;9798350344851

A speech spoofing countermeasure (CM) that discriminates between unseen spoofed and bona fide data requires diverse training data. While many datasets use spoofed data generated by speech synthesis systems, it was recently found that data vocoded by neural vocoders were also effective as the spoofed training data. Since many neural vocoders are fast in building and generation, this study used multiple neural vocoders and created more than 9,000 hours of vocoded data on the basis of the VoxCeleb2 corpus. This study investigates how this large-scale vocoded data can improve spoofing countermeasures that use data-hungry self-supervised learning (SSL) models. Experiments demonstrated that the overall CM performance on multiple test sets improved when using features extracted by an SSL model continually trained on the vocoded data. Further improvement was observed when using a new SSL distilled from the two SSLs before and after the continual training. The CM with the distilled SSL outperformed the previous best model on challenging unseen test sets, including the ASVspoof 2019 logical access, WaveFake, and In-the-Wild.

关键词： anti-spoofing presentation attack detection countermeasure logical access neural vocoder

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LEARNING FROM EASY TO HARD: MULTI-TASK LEARNING WITH data SCHEDULING 49

LEARNING FROM EASY TO HARD: MULTI-TASK LEARNING WITH DATA SC...

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49th IEEE international conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Liu, Zeyu Chai, Heyan Liao, Qing Harbin Inst Technol Shenzhen Sch Comp Sci & Technol Harbin Peoples R China Peng Cheng Lab Shenzhen Peoples R China

ISBN: (纸本)9798350344868;9798350344851

Multi-task learning (MTL) aims to enhance the performance of all tasks by sharing the learned representations. However, sharing the representations may lead to performance degradation due to task conflicts. Existing MTL methods mainly focus on the relationship between tasks, ignoring that data samples can contribute differently to tasks. Inspired by curriculum learning, we consider the varying effects of data samples on tasks. We propose a novel method, Sample-Level data Scheduling (SLDS) for MTL, which adopts a curriculum learning strategy. SLDS gradually feeds the model with data ranging from easy to hard. Samples that lead to fewer task conflicts and smaller loss values are considered easy samples and given more weight. Throughout the training process, the model is initially trained with easy data and gradually exposed to hard data. We compare SLDS with several state-of-the-art MTL methods, and experimental results show the effectiveness of our method.

关键词： multi-task learning data scheduling task conflicts

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