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检索条件"任意字段=2024 IEEE International Conference on Visual Communications and Image Processing, VCIP 2024"

共 2510 条记录，以下是31-40 订阅

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Map-Free visual Relocalization Enhanced by Instance Knowledge and Depth Knowledge

Map-Free Visual Relocalization Enhanced by Instance Knowledg...

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international conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Mingyu Xiao Runze Chen Haiyong Luo Fang Zhao Fan Wu Hao Xiong Xuepeng Ma Juan Wang Beijing University of Posts and Telecommunications Bejing China Institute of Computing Technology Chinese Academy of Sciences Bejing China Shouguang Cheng Zhi Feng Xing Technology Co. Ltd. ShanDong China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Map-free visual relocalization computes camera pose using only a query image and a reference image. Therefore, it is hindered by challenges in feature-point matching and the absence of scale information in monocular images. These issues may cause significant rotational and metric errors, leading to localization failures. To address these challenges, we propose a map-free visual relocalization method enhanced with instance knowledge and depth knowledge. By utilizing instance-based matching, our approach improves the robustness of feature-point matching by focusing on relevant regions across scenes. Additionally, our depth estimation techniques provide reliable depth knowledge from a single image, improving scale recovery and reducing translation errors. Our method surpasses the previous state-of-the-art by 1.071m and 13.593° on the translation error and rotation error, respectively. Furthermore, we are also one of the winners in the Map-free Workshop & Challenge (ECCV2024), underscoring its superiority compared to concurrent approaches.

关键词： Location awareness Instance segmentation visualization Translation Accuracy Three-dimensional displays Depth measurement Signal processing Robustness Speech processing

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LatentNeuroNet: A Text-Conditioned Stable Diffusion Framework for Reconstructing visual Stimuli from fMRI 8th

LatentNeuroNet: A Text-Conditioned Stable Diffusion Framewor...

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8th international conference on Advances in Computing and Data Sciences, ICACDS 2024

作者： Battula, Shreyas Kirithivasan, Shyam Krishna Soori, Aditi Ramesh, Richa Srinath, Ramamoorthy Department of Computer Science and Engineering PES University Karnataka Bangalore India

ISBN: (纸本)9783031709050

The human brain, among the most complex and mysterious aspects of the body, harbours vast potential for extensive exploration. Unravelling these enigmas, especially within neural perception and cognition, delves into the realm of neural decoding. Harnessing advancements in generative AI, particularly in the image processing domain, seeks to elucidate how the brain comprehends visual stimuli perceived by humans. The paper endeavours to reconstruct human-perceived visual stimuli using Functional Magnetic Resonance Imaging (fMRI). This fMRI data is then processed through pre-trained deep-learning models to recreate the stimuli. Introducing a new architecture named LatentNeuroNet, the aim is to achieve the utmost semantic fidelity in stimuli reconstruction. The approach employs a Latent Diffusion Model (LDM), emphasizing semantic accuracy and generating superior-quality outputs. Text conditioning within the LDM’s denoising process is handled by extracting text from the brain’s ventral visual cortex region. This extracted text undergoes processing through a Bootstrapping Language-image Pre-training (BLIP) encoder before it is injected into the denoising process. In conclusion, a successful architecture is developed that reconstructs the visual stimuli perceived and finally, this research provides us with enough evidence to identify the most substantial regions of the brain responsible for perception. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Semantics

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VisionLingua: Empowering Multimodal Understanding with Cutting-Edge Language Models 4th

VisionLingua: Empowering Multimodal Understanding with Cutt...

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4th international conference on Advanced Network Technologies and Intelligent Computing, ANTIC 2024

作者： Kamboj, Deepika Gola, Kamal Kumar Arya, Shikha UPES Uttarakhand Dehradun India COER University Uttarakhand Roorkee India Indian Institute of Technology Uttarakhand Roorkee India

ISBN: (纸本)9783031837951

Recent developments in large language models (LLMs) have demonstrated significant progress in both language understanding and generation. In particular, GPT-4, a model capable of processing both text and images, presents challenges in understanding its internal operations. To investigate this, we propose VisionLingua, a model that integrates a fixed visual encoder with the Vicuna language model through a projection layer. Our study shows that aligning a visual module with a state-of-the-art language model unlocks a broad range of capabilities, including detailed image description, conversion of hand-drawn sketches into digital formats, interpretation of complex visual phenomena, and detection and resolution of issues in images. In early experiments, VisionLingua’s performance was hindered by the limited size of the training dataset, resulting in inconsistent text outputs. To improve performance, we implemented a second training phase using an expanded dataset with detailed image descriptions, which significantly enhanced the model’s ability to produce coherent and accurate text outputs. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： visual languages

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3rd international conference on Electronic Governance with Emerging Technologies, EGETC 2024

3rd International Conference on Electronic Governance with E...

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3rd international conference on Electronic Governance with Emerging Technologies, EGETC 2024

ISBN: (纸本)9783031770289

The proceedings contain 17 papers. The special focus in this conference is on Electronic Governance with Emerging Technologies. The topics include: Ecological Development of a Novel Machine Learning Technique for Electricity Consumption and Cost Prediction in Cloud Computing;blockchain Based Decentralized Approach for Securing Fog Computing Environment;Enhancing Face Spoofing Detection Via CNN Model Integration with Normalized Features;Study of ZigBee-Based Communication to Share Operative Weather Information Between UASs in the Frame of Smart Cities Concept;automating Exam Assessment Through Digital Transformation and image processing;an Analysis of Ethical Dimension of Machine Learning Models in Software Defect Prediction in Healthcare Sector;leaf Diseases Detection in Peach Using EfficientNet;medInsight: A Personalized Prescription Recommendation Using Machine Learning;intelligent Machine Learning for Cybersecurity: Anomaly Detection in Network Intrusion Systems and Beyond;Enhancing Cyber Resilience: Implementing DFMCAI for Threat Detection and Analysis;forecasting Future Credit Card Delinquencies: Leveraging Data Tables and visual Analysis for Enhanced Accuracy;navigating the Strategic Landscape: An In-Depth Review of the Strategic Planning Process;exploring Text Vectorization on the Polarity Detection of Spanish Comments;Evolutionary Optimization Techniques for the Design of Three-Dimensional UAV’s Antenna Arrays;cooperative Multi-agent Pursuit-Evasion Using Convolutional Neural Networks.

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Residential Real Estate image Classification for Property Valuation

Residential Real Estate Image Classification for Property Va...

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28th international conference on image processing, Computer Vision, and Pattern Recognition, IPCV 2024, and 23rd international conference on Information and Knowledge Engineering, IKE 2024, held as part of the World Congress in Computer Science, Computer Engineering and Applied Computing, CSCE 2024

作者： Nejad, Mehrdad Ziaee Naderpour, Mohsen Behbood, Vahid Ramezani, Fahimeh Lu, Jie 15 Broadway UltimoNSW2007 Australia

ISBN: (纸本)9783031859328

Residential real estate price is one of the key components of our economic developments and has also been a major concern of the public, bank industry, government, and investors. The accurate estimation of the sale price and its changes have an important role in the decision-making of related departments and organizations. In Australia, one of the biggest investments for people is in residential real estate. Therefore, many studies and research works have been carried out to build an automated valuation model to predict sale prices of residential properties accurately as much as possible. Automatic and accurate image classification of residential real estate plays an important role in property valuation and decision making of both sellers and buyers. It can be used in real estate online websites to organize the images for each property or used as a component in a visual decision support system for predicting the property sale prices based on property images. As convolutional image classification models show valuable performance in comparison with traditional models, a convolutional classification model is developed in this paper which creates a highly reliable classification component to be used in the corresponding research areas. The performance of the proposed model is investigated through a real dataset of New Sales Wales, Australia. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Convolutional neural networks

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Enhanced image Deblurring with the Fusion of Generative Adversarial Networks and Transformer Models 1st

Enhanced Image Deblurring with the Fusion of Generative Adve...

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1st international conference on Innovation and Emerging Trends in Computing and Information Technologies, IETCIT 2024

作者： Ranjan, Arti Ravinder, M. New Delhi India Department of Computer Science and Engineering Galgotias College of Engineering and Technology Greater Noida India

ISBN: (纸本)9783031808418

In the domain of image processing, deblurring remains a challenging task, particularly in restoring high-fidelity details from blurred images. This paper introduces a novel approach that synergizes the strengths of Generative Adversarial Networks (GANs) and Transformer models to address this challenge. Our methodology leverages the generative capability of GANs to produce realistic and sharp images, while incorporating the Transformer’s prowess in capturing long-range dependencies and intricate details within images. This adversarial training regime is designed to refine the model’s ability to generate deblurred images that are not only accurate in detail but also high in perceptual quality. Through extensive experiments on various datasets, our model demonstrates superior performance in deblurring, outperforming existing state-of-the-art methods in terms of both objective metrics and subjective visual quality. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Generative adversarial networks

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

8th International Conference on Life System Modeling and Sim...

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

ISBN: (纸本)9789819602315

The proceedings contain 158 papers. The special focus in this conference is on Life System Modeling and Simulation and Intelligent Computing for Sustainable Energy and Environment. The topics include: A Method for Evaluating the Operating Health of Wind Turbines Under Wake Effect;toward Next-Generation Buildings: A Review of Renewable Energy Integration and Intelligent Building Energy Management Technologies;improving the Construction of a Multi-modal Underwater image Recognition System for Anomaly Detection in Nuclear Power Plant Cooling Source Areas;A Novel Anti-noise Fault Diagnosis Method for Nuclear Energy Steam Turbine Based on VCformer;Short-Term Photovoltaic Power Forecasting Using Multi-timescale Information Based FFTformer Model;wind Power Forecasting Model Based on Feature processing and Deep Hybrid Kernel Extreme Learning Machine;optimal User-Side Energy Arbitrage Strategy in Electricity Market with Accurate Battery Model Using Benders Decomposition;a Novel Distributed Economic Dispatch Method for Smart Grid with Time-Varying Feedback Gain;benefits, Barriers, and Human Factors of V2X Implementation – A Brief Review;a General Pattern of Permanent Magnet Arrangement for Design Optimization of a Reluctance Magnetic Gear with Enhanced Torque Density for Electric Vehicles;wind Power Scheduling Deviation Compensation Based on Dual-Frequency Pulse Control;a Comprehensive Simulation and Validation of Single Particle Aging Mechanism Model for Lithium-Ion Batteries;semi-supervised State of Health Estimation for Lithium-Ion Batteries via Dynamical Self-encoding;a Reduce-Order Model to Understand the Multiscale Coupling of Battery Electrochemical-Thermal Performance;RUL Prediction for Lithium-Ion Batteries Based on Sequence Decomposition and Transformer Networks;An Estimation Method of State of Health of Sodium-Ion Batteries Based on TCN.

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

8th International Conference on Life System Modeling and Sim...

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

ISBN: (纸本)9789819602247

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

8th International Conference on Life System Modeling and Sim...

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

ISBN: (纸本)9789819602933

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Improving the Construction of a Multi-modal Underwater image Recognition System for Anomaly Detection in Nuclear Power Plant Cooling Source Areas 8th

Improving the Construction of a Multi-modal Underwater Image...

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

作者： Huang, Yu Wang, Kai Gu, Yuntao Zhou, Chaofan Guo, Yuanjun Yang, Zhile China Nuclear Industry Maintenance Co. Ltd. Shenzhen Branch Shenzhen China Taiyuan University of Technology Taiyuan030024 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China

ISBN: (纸本)9789819602315

The cooling facilities of nuclear power plants are crucial components for transferring the accumulated heat from the reactor to the external environment. However, the complex structure of these facilities makes traditional manual anomaly detection methods inefficient, time-consuming, and poses certain risks to human safety. Therefore, this paper proposes a system for anomaly detection in the cooling source areas of nuclear power plants based on improved multi-modal underwater image recognition. The system utilizes deep learning and image processing techniques to denoise, compensate for illumination, and correct water flow in collected images of the cooling source areas. Wavelet-based noise removal techniques are applied to further enhance image clarity, providing accurate inputs for machine vision algorithms. By training an improved convolutional neural network model, real-time automatic identification and classification of underwater anomalies such as foreign objects and pipeline cracks are achieved, significantly improving the monitoring efficiency and safety of the cooling source areas in nuclear power plants. Comparative analysis with actual cases validates the excellent stability and accuracy of the proposed method in handling underwater operation images in the cooling source areas of nuclear power plants. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Nuclear power plants

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