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A Lightweight Network of Groupwise Separable Convolution and Vision Transformer for Hyperspectral Image Classification 3

A Lightweight Network of Groupwise Separable Convolution and...

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3rd international conference on Optics and machine Vision, ICOMV 2024

作者： Zhao, Zhuoyi Xu, Xiang School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China The Artificial Intelligence and Computer Vision Laboratory University of Electronic Science and Technology of China Zhongshan Institute Zhongshan China

ISBN: (纸本)9781510680319

Hyperspectral image (HSI) data consists of images with numerous contiguous spectral bands and promotes the extensive applications in the field of remote sensing. Recent approaches based on Vision Transformer (ViT) have achieved remarkable performance in HSI classification tasks due to their ability to extract global spatial features and model long-range dependencies. However, ViT has complex network structure, training is challenging and lacks adequate consideration of local spatial and spectral receptive fields in hyperspectral data. To solve the problems above, we propose a lightweight network model known as the Groupwise Separable Convolution and Vision Transformer (GSCViT). Firstly, we introduce a parameter-free attention for spectral calibration (SC). Then, we meticulously design a novel convolutional approach named Groupwise Separable Convolution (GSC), which greatly reduce the number of convolutional kernel parameters and effectively capture local spatial-spectral information in HSI data. In addition, we employ Groupwise Separable Multi-Head Self-Attention (GSSA) to replace the traditional Multi-Head Self-Attention (MSA) in ViT, thus can simultaneously attend to local and global spatial features in HSI with lower computational burden. Experiments on two benchmark HSI datasets demonstrate that our GSCViT model achieves excellent accuracy with relatively small training samples and outperforms some existing HSI classification algorithms. © 2024 SPIE.

关键词： Convolution

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3rd EAI international conference on Edge Computing and IoT, EAI ICECI 2022

3rd EAI International Conference on Edge Computing and IoT, ...

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3rd EAI international conference on Edge Computing and IoT, EAI ICECI 2022

ISBN: (纸本)9783031289897

The proceedings contain 21 papers. The special focus in this conference is on Edge Computing and IoT. The topics include: Evaluation of Higher Education System;defense Mechanisms Against Audio Adversarial Attacks: Recent Advances and Future Directions;an Empirical Study of Worldwide Plastic Waste Mitigation;prediction for Surface Subsidence of Shield Construction in Water-Rich Sand Egg Stratum Based on Edge intelligence;highly Accurate Dynamic Gesture recognition Method Based on Edge intelligence;adversarial Example Attacks in Internet of Things (IoT);training Node Screening in Decentralized Trusted Federated Learning;exploration and Practice of Course Homework Metaverse Based on Extended Reality Under Edge Computing;federated Learning Based User Scheduling for Real-Time Multimedia Tasks in Edge Devices;the Data Exchange Protocol over Multi-chain Blockchain Using Zero-Knowledge Proof;a Co-caching Strategy for Edges Based on Federated Learning and Regional Prevalence;LSTM-DAM: Malicious Network Traffic Prediction for Cloud Manufacturing System;a Hybrid Task Offloading and Service Cache Scheme for Vehicular Edge Computing;on Enhancing Transmission Performance for IoV Based on Improved Greedy Algorithm;Precise Segmentation on Poly-Yolo, YoloV5 and FCN;Research on DAG Based Consensus Mechanism for Adjustable Load Metering Data;a Detection and Information Processing Model Based on an Automatic Mechanism for Tax Payment Control in Developing Countries;IEC-FOF: An Industrial Electricity Consumption Forecasting and Optimization Framework;demons Hidden in the Light: Unrestricted Adversarial Illumination Attacks.

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3rd international Joint conference on Discrete Geometry and Mathematical Morphology, DGMM 2024

3rd International Joint Conference on Discrete Geometry and ...

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3rd international Joint conference on Discrete Geometry and Mathematical Morphology, DGMM 2024

ISBN: (纸本)9783031577925

The proceedings contain 34 papers. The special focus in this conference is on Discrete Geometry and Mathematical Morphology. The topics include: Bijective Digitized 3D Rotation Based on Beam Shears;new Characterizations of Full Convexity;decomposition of Rational Discrete Planes;differential Maximum Euclidean Distance Transform Computation in Component Trees;construction of Fast and Accurate 2D Bijective Rigid Transformation;digital Calculus Frameworks and Comparative Evaluation of Their Laplace-Beltrami Operators;fitting Egg-Shapes to Discretized Object Boundaries;construction of Tilings with Transitivity Properties on the Square Grid;some Geometric and Tomographic Results on Gray-Scale Images;a Khalimsky-Like Topology on the Triangular Grid;group Equivariant Networks Using Morphological Operators;an Algorithm to Train Unrestricted Sequential Discrete Morphological Neural Networks;discovering Repeated patterns from the Onsets in a Multidimensional Representation of Music;the Lattice Overparametrization Paradigm for the machine Learning of Lattice Operators;convex Optimization for Binary Tree-Based Transport Networks;training Morphological Neural Networks with Gradient Descent: Some Theoretical Insights;HaarNet: Large-Scale Linear-Morphological Hybrid Network for RGB-D Semantic Segmentation;Nonlinear Representation Theory of Equivariant CNNs on Homogeneous Spaces Using Group Morphology;building the Topological Tree of Shapes from the Tree of Shapes;end-to-End Ultrametric Learning for Hierarchical Segmentation;out-of-Core Attribute Algorithms for Binary Partition Hierarchies;multi-scale Component-Tree: A Hierarchical Representation for Sparse Objects;an Approach to Colour Morphological Supremum Formation Using the LogSumExp Approximation;image Segmentation by Hierarchical Layered Oriented Image Foresting Transform Subject to Closeness Constraints;elastic Analysis of Augmented Curves and Constrained Surfaces;morse Frames;morse Sequences;1-Attempt and Equivalent Thinni

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Modeling of Dengue Fever Outbreaks Using machine Learning Techniques 15th

Modeling of Dengue Fever Outbreaks Using Machine Learning Te...

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15th international conference on Soft Computing and pattern recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2023

作者： Singh, Divyanshi Harshita Srivastava, Ananya Dash, Yajnaseni Abraham, Ajith School of Computer Science Engineering and Technology Bennett University UP Greater Noida India School of Artificial Intelligence Bennett University UP Greater Noida India School of Artificial Intelligence Sai University Chennai India

ISBN: (纸本)9783031810794

Dengue is a life-threatening disease that has been increasing at an unprecedented rate in India as well as around the globe. The disease is affected by various factors such as population, urbanization, as well as climate change. Dynamic transmission of dengue fever is majorly influenced by climate change. Rising temperatures, altered rainfall patterns, and changing ecosystems contribute to the spread and severity of the disease. Random Forest, Long Short-Term Memory (LSTM), k-Nearest Neighbors (KNN), and LightGBM, are used here to understand and predict dengue fever dynamics, aiding in developing effective prevention and control strategies. This study focuses on the importance of interdisciplinary approaches, integrating artificial intelligence, climatology, epidemiology, ecology, and public health, to lessen the impact of climate change on dengue fever transmission and safeguard global health security. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Global warming

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Biomedical Interventions in Precision Medicine for Diabetics 3

Biomedical Interventions in Precision Medicine for Diabetics

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3rd international conference on Smart Technologies, Communication and Robotics, STCR 2023

作者： Madhumitha, A. Dhananjayan, V. Bannari Amman Institute of Technology Dept. of Computer Science and Bussiness System Tamil Nadu Sathyamangalam India Bannari Amman Institute of Technology Dept. of Artificial Intelligence and Machine Learning Tamil Nadu Sathyamangalam India

ISBN: (纸本)9798350370867

Precision medicine is the need of the hour strategy that deals with precision from diagnosis to treatment. There is a growing need for continuous monitoring of blood glucose levels and an effective algorithm to determine the right insulin dosages to achieve precision medicine for diabetes. This work intends to review the impact and importance of biomedical interventions in precision medicine for diabetes. It addresses the barriers that persist in practicing precision medicine for diabetes by strengthening the techniques of precision diagnosis and prognosis, precision therapeutics, precision treatments, and precision monitoring using predictive algorithms. The review emphasizes the significance of biomedical interventions in advancing the future directions of precision medicine for diabetes, including the integration of clinical trials with large datasets and continuous evaluation and monitoring of patients through regular measurements of blood glucose levels. By focusing on these biomedical interventions, this review aims to provide insights into the role of precision medicine in diabetes and its potential for improving patient outcomes. © 2023 IEEE.

关键词： Diagnosis

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Multi-teacher Knowledge Distillation for End-to-End Text Image machine Translation 17th

Multi-teacher Knowledge Distillation for End-to-End Text Ima...

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17th international conference on Document Analysis and recognition (ICDAR)

作者： Ma, Cong Zhang, Yaping Tu, Mei Zhao, Yang Zhou, Yu Zong, Chengqing Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Multimodal Artificial Intelligence Beijing 100190 Peoples R China Zhongke Fanyu Technol Co Ltd Fanyu AI Lab Beijing 100190 Peoples R China Samsung Res China Beijing SRC B Beijing Peoples R China

ISBN: (纸本)9783031416750;9783031416767

Text image machine translation (TIMT) has been widely used in various real-world applications, which translates source language texts in images into another target language sentence. Existing methods on TIMT are mainly divided into two categories: the recognition-then-translation pipeline model and the end-to-end model. However, how to transfer knowledge from the pipeline model into the end-to-end model remains an unsolved problem. In this paper, we propose a novel Multi-Teacher Knowledge Distillation (MTKD) method to effectively distillate knowledge into the end-to-end TIMT model from the pipeline model. Specifically, three teachers are utilized to improve the performance of the end-to-end TIMT model. The image encoder in the end-to-end TIMT model is optimized with the knowledge distillation guidance from the recognition teacher encoder, while the sequential encoder and decoder are improved by transferring knowledge from the translation sequential and decoder teacher models. Furthermore, both token and sentence-level knowledge distillations are incorporated to better boost the translation performance. Extensive experimental results show that our proposed MTKD effectively improves the text image translation performance and outperforms existing end-to-end and pipeline models with fewer parameters and less decoding time, illustrating that MTKD can take advantage of both pipeline and end-to-end models. Our codes are available at: https://***/EriCongMa/MTKD_TIMT.

关键词： Text Image machine Translation Knowledge Distillation machine Translation

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15th international conference on Intelligent Human Computer Interaction, IHCI 2023

15th International Conference on Intelligent Human Computer ...

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15th international conference on Intelligent Human Computer Interaction, IHCI 2023

ISBN: (纸本)9783031538261

The proceedings contain 71 papers. The special focus in this conference is on Intelligent Human Computer Interaction. The topics include: Cross Cultural Comparison of Emotional Functional Networks;emotion recognition Using Phase-Locking-Value Based Functional Brain Connections Within-Hemisphere and Cross-Hemisphere;context-Aware Facial Expression recognition Using Deep Convolutional Neural Network Architecture;exploring Multimodal Features to Understand Cultural Context for Spontaneous Humor Prediction;development of Pneumonia Patient Classification Model Using Fair Federated Learning;artificial intelligence in Medicine: Enhancing Pneumonia Detection Using Wavelet Transform;Maximizing Accuracy in AI-Driven pattern Detection in Cardiac Care;Development of IMU Sensor-Based XGBoost Model for Patients with Elbow Joint Damage;application of Daubechies Wavelets in Digital Processing of Biomedical Signals and Images;adopting Pre-trained Large Language Models for Regional Language Tasks: A Case Study;An Integrated System for Stroke Rehabilitation Exercise Assessment Using KINECT v2 and machine Learning;gastric Ulcer Detection in Endoscopic Images Using MobileNetV3-Small;exploring Quantum machine Learning for Early Disease Detection: Perspectives, Challenges, and Opportunities;subject-Independent Brain-Computer Interfaces: A Comparative Study of Attention Mechanism-Driven Deep Learning Models;PPHR: A Personalized AI System for Proactive Robots;classifying Service Robots in Commercial Places Based on Communication: Design Elements by Level of Communication;Cascade Mentoring Experience to Engage High School Learners in AI and Robotics Through Project-Based Learning;leveraging Human-machine Interactions for Computer Vision Dataset Quality Enhancement;A Comprehensive Survey on AgriTech to Pioneer the HCI-Based Future of Farming;roboRecycle Buddy: Enhancing Early Childhood Green Education and Recycling Habits Through Playful Interaction with a Social Robot;Text Mining Based GPT M

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The Privacy Computing for Digital Economy Development under New Technology Based on Spatial-Temporal Information Matrix, Especially among RCEP Nations 3

The Privacy Computing for Digital Economy Development under ...

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3rd international conference on pattern recognition and machine Learning, PRML 2022

作者： Liu, Haitao Zheng, Shenjun Hong, Yong Cao, Yujuan Lu, Yun Tian, Tian Guangxi Artificial Intelligence and Big Data Applying Institute Nanning530201 China Hangzhou ChinaOly Technology Co. Ltd. Hangzhou310015 China Wuhan University State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan430079 China Guangxi Academy of Social Sciences Nanning530201 China

ISBN: (数字)9781665499507

ISBN: (纸本)9781665499507

With the coming of intelligent era, the wide using of new generation information technology, such as Internet on Things, AI, Big data and Cloud computing, digital economic development is more and more prosperous for every economic entity, specially, for some emerging economic entities, such as RCEP nations. However, the problem of objective evaluation of ability of digital economic development of different nations and dependence of digital economic development among each nation are very hard but necessary under not leaking digital economic data of all parts. For solving this problem, an improvement Meta Learning approach was proposed creatively which constructed temporal dimension factor and spatial dimension factor based on spatial-temporal information matrix method. It could make knowledge transfer from source network to target network according to the orthogonal rule between temporal dimension factor and spatial dimension factor. 3 different type and smart test ways were designed in order to validate the performance of the approach of this paper comprehensively. Digital economic development data of RECP nations were collected and employed for testing. The amount and accuracy of knowledge transfer from different source network to various target network were validated one by one. The results not only validate the effectiveness of improving Meta Learning approach of this article but also reveal that the diversity of digital economy development among RECP nations but impacting tightly each other. Moreover, there also have relative contribution on opening knowledge transfer from source network to target network under privacy data not be leaked. This content would be researched at more complex industrial data forward. © 2022 IEEE.

关键词： Economic and social effects

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Lithium-Ion Battery Inspection System for EVs 3rd

Lithium-Ion Battery Inspection System for EVs

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3rd international conference on Intelligent Systems and Sustainable Computing, ICISSC 2023

作者： Haswanth, Kairam Ram Malladi, Jyothi Swaroop Prabhu, S. Nagendra Dinesh, G. Department of Computational Intelligence School of Computing SRM Institute of Science and Technology KTR Chennai India Lovely Professional University Punjab Phagwara India

ISBN: (纸本)9789819783540

With the increase in the speed of development, there has been a dire need to make the development as efficient as possible. Also, the increased depletion of gasoline resources has forced automobile industries to switch to electric vehicles [1]. However, the switch is not so easy as the batteries used in the electric vehicles are not as good at times giving rise to dying down, wearing out, and even fire breakout without any prior intimation. In this paper, we are trying to solve that problem for electric vehicles and make a detailed study of the automated methods to check for the lithium-ion batteries that are widely used in the vehicles. In this paper, we will be discussing the implementation of machine learning in the domain and solving the problem of EV batteries [2] and helping to generate a smart system to check for the health and the state of charge of the lithium-ion batteries. With the use of machine learning algorithms like XG-Boost, Random Forest classifier, time series analysis algorithms and Deep learning algorithms like RCNN and deep LSTM provide an ensembled result output for the same. The accuracy of the projected module is expected to be much more than the existing systems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Petroleum deposits

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15th international conference on Intelligent Human Computer Interaction, IHCI 2023

15th International Conference on Intelligent Human Computer ...

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15th international conference on Intelligent Human Computer Interaction, IHCI 2023

ISBN: (纸本)9783031538292

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