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检索条件"任意字段=Proceedings - 3rd International Conference on Distributed Computing Systems."

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Intelligent Image Captioning with InceptionV3, LSTM, and PySpark Integration 3

Intelligent Image Captioning with InceptionV3, LSTM, and PyS...

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3rd international conference on Intelligent and Innovative Technologies in computing, Electrical and Electronics, IITCEE 2025

作者： Kurian, Thanu Mathew, Jimsha K. Syam Dev, R.S. Anand, P.K. Vignesh, A. Rakshith, B.S. New Horizon College of Engineering Dept of Artificial Intelligence and Machine Learning Bengaluru India

ISBN: (纸本)9798331515911

Image captioning is a challenging task in artificial intelligence that involves generating descriptive captions for images automatically. In this project, we propose a novel approach leveraging advanced technologies such as PySpark, LSTM, and InceptionV3 to develop an effective image captioning system. We harness the power of PySpark, a distributed computing framework, to efficiently process large-scale image datasets and extract high-level features from images using the InceptionV3 convolutional neural network (CNN) model. These features capture the semantic information present in the images and serve as input to the caption generation model. The caption generation model utilizes LSTM neural network as the decoder component. LSTM is well-suited for sequential data processing and is capable of generating coherent and contextually relevant captions based on the extracted image features. The InceptionV3 model acts as the encoder, extracting meaningful visual features from input images, while the LSTM decoder generates captions by decoding these features into natural language descriptions. This multimodal approach enables the model to understand and describe the content of images accurately. Through experimentation and evaluation on diverse image datasets, our proposed system demonstrates promising results in generating accurate and human-like captions for a wide range of images. By integrating PySpark, LSTM, and InceptionV3, our image captioning system achieves state-of-the-art performance, highlighting the effectiveness of leveraging advanced technologies in solving complex AI tasks. © 2025 IEEE.

关键词： Convolutional neural networks

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3rd international conference on Smart Technologies and Innovation Management, MTYMEX 2024

3rd International Conference on Smart Technologies and Innov...

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3rd international conference on Smart Technologies and Innovation Management, MTYMEX 2024

ISBN: (纸本)9783031649561

The proceedings contain 15 papers. The special focus in this conference is on Smart Technologies and Innovation Management. The topics include: Prospective Directions in the Computer systems.Industry Foundation Classes (IFC) Shaping Data Exchange for Cities Sustainability and Resilience;a Proposal of Model Combining Semantic Analysis and Knowledge Graph for Question Answering System in Vietnamese Law of Science and Technology;trends and Innovative Tactics in Startup Innovation: A Survey;interactive Web Mapping for Geolocation of Socio-community Infrastructure in a Developing Country;development of Digital Capabilities for E-commerce Agribusiness: An Exploratory Research;a Social-Software-Based Telemedicine Information System for Facilitating Healthcare Services;lab-to-Market Product Innovation: Implications of Using a Translational Research & Development Model and Methodology;a Multilayered Process Framework for Predicting Students’ Academic Performance in Open and Distance Learning;a New Notification System for Tracking Ethereum Transactions with Social Media Software;A Secure Consortium-Blockchain-Enabled Communication Scheme for DNA-Based Smart Health systems.review on Machine Learning for Zero-Day Exploit Detection and Response;A Review of AI in Spear Phishing Defense: Detecting and Thwarting Advanced Email Threats;energy-Efficient Dynamic Adaptive Encryption for Low-Resource Internet of Things.

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A Comprehensive and Systematic Analysis of One-Way Hashing and Its Advancements 3

A Comprehensive and Systematic Analysis of One-Way Hashing a...

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3rd international conference on Intelligent systems. Advanced computing, and Communication, ISACC 2025

作者： Chakraborty, Abhilash Biswas, Anupam National Institute of Technology Silchar Department of Computer Science and Engineering Assam Silchar 788010 India

ISBN: (纸本)9798331523893

Cryptographic hash functions are fundamental to secure digital interactions. This paper surveys one-way hashing, covering theoretical foundations, historical developments, cryptanalytic challenges, and widely trusted standards like SHA-2, SHA-3, and BLAKE2/BLAKE3. It also explores experimental designs and proprietary functions enhancing password protection, IoT security, and blockchain mechanisms. The study examines tensions between performance and security, classical versus post-quantum resilience, and theoretical rigor versus practical engineering. Hashing is both a mature discipline and an evolving frontier, poised to adapt to changing computational paradigms and sophisticated adversarial methods while meeting growing demands for data integrity and authenticity guarantees. © 2025 IEEE.

关键词： Blockchain Integrity Chaos-Based Hashing Collision Resistance Complexity-Theoretic Foundations IoT and Lightweight Hashes Merkle-Damgård Construction One-Way Hashing Post-Quantum Security Preimage Resistance Sponge Constructions

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2nd international Workshop on Fairness of AI in Medical Imaging, FAIMI 2024, and 3rd international Workshop on Ethical and Philosophical Issues in Medical Imaging, EPIMI 2024, Held in Conjunction with the international conference on Medical Image computing and Computer Assisted Interventions, MICCAI 2024

2nd International Workshop on Fairness of AI in Medical Imag...

引用

2nd international Workshop on Fairness of AI in Medical Imaging, FAIMI 2024, and 3rd international Workshop on Ethical and Philosophical Issues in Medical Imaging, EPIMI 2024, Held in Conjunction with the international conference on Medical Image computing and Computer Assisted Interventions, MICCAI 2024

ISBN: (纸本)9783031727863

The proceedings contain 17 papers. The special focus in this conference is on Fairness of AI in Medical Imaging. The topics include: Dataset Distribution Impacts Model Fairness: Single Vs. Multi-task Learning;AI Fairness in Medical Imaging: Controlling for Disease Severity;Fair and Private CT Contrast Agent Detection;Mitigating Overdiagnosis Bias in CNN-Based Alzheimer’s Disease Diagnosis for the Elderly;Positive-Sum Fairness: Leveraging Demographic Attributes to Achieve Fair AI Outcomes Without Sacrificing Group Gains;all You Need Is a Guiding Hand: Mitigating Shortcut Bias in Deep Learning Models for Medical Imaging;exploring Fairness in State-of-the-Art Pulmonary Nodule Detection Algorithms;quantifying the Impact of Population Shift Across Age and Sex for Abdominal Organ Segmentation;BMFT: Achieving Fairness via Bias-Based Weight Masking Fine-Tuning;using Backbone Foundation Model for Evaluating Fairness in Chest Radiography Without Demographic Data;do Sites Benefit Equally from distributed Learning in Medical Image Analysis?;Cycle-GANs Generated Difference Maps to Interpret Race Prediction from Medical Images;On Biases in a UK Biobank-Based Retinal Image Classification Model;investigating Gender Bias in Lymph-Node Segmentation with Anatomical Priors;Assessing the Impact of Sociotechnical Harms in AI-Based Medical Image Analysis;Practical and Ethical Considerations for Generative AI in Medical Imaging.

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proceedings - 33rd international conference on distributed computing systems. ICDCSW 2013

Proceedings - 33rd International Conference on Distributed C...

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33rd IEEE international conference on distributed computing systems.Workshops, ICDCSW 2013

The proceedings contain 70 papers. The topics discussed include: mining web technical discussions to identify malware capabilities;malware similarity identification using call graph based system call subsequence features;the middle east under malware attack dissecting cyber weapons;anonymous data forwarding in human associated delay tolerant networks;a scalable and privacy-preserving named data networking architecture based on bloom filters;fault-aware flow control and multi-path routing in wireless sensor networks;attacking tor through unpopular ports;a method to automatically filter log evidences for intrusion forensics;secure cache provision: provable DDOS prevention for randomly partitioned services with replication;and privacy preserving query answering in peer data management systems.

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An iterated greedy algorithm based on NSGA-II for distributed hybrid flow shop scheduling problem 3

An iterated greedy algorithm based on NSGA-II for distribute...

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3rd international conference on Communications, Information System, and Data Science, CISDS 2024

作者： Liu, Dandan Liang, Xu Zou, Zhiyuan School of Computing Beijing Information Science and Technology University Beijing China

ISBN: (数字)9781510688322

ISBN: (纸本)9781510688315

The distributed hybrid flow shop scheduling problems (DHFSP) widely exist in various industrial production processes, and thus have received widespread attention. However, studies on HFSP considering green objective in distributed production environment are quite limited. Therefore, this paper investigated a distributed hybrid flow shop scheduling problem with objectives of minimization the makespan and total energy consumption (TEC). To solve it, an iterated greedy algorithm based on NSGA-II (NSGAIG) is developed. In the proposed algorithm, a random initialization strategy is used to generate the initial solution. Then, starting from the population initialization, a multi-objective local search is carried out for the current optimal solution in the population to obtain the global optimal solution. Next, random variation method is used to increase the exploration space of the algorithm. Finally, the proposed NSGAIG algorithm is compared with other multi-objective optimization algorithms. Experimental results indicate that the proposed NSGAIG outperforms its compared algorithms in solving this problem. © 2025 SPIE.

关键词： Optimization algorithms

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3rd international conference on Advances in computing Research, ACR 2025

3rd International Conference on Advances in Computing Resear...

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3rd international conference on Advances in computing Research, ACR 2025

ISBN: (纸本)9783031876462

The proceedings contain 41 papers. The special focus in this conference is on Advances in computing Research. The topics include: Understanding GPU Architecture Influences on Low-Precision Deep Reinforcement Learning Performance;an Explainable Predictive Model for the Detection of Mental Health Conditions in the Workplace;optimizing Bipartite Matching with Interleaved and Injective Mappings: Implementing and Evaluating the k-Swap Heuristic;ioT-Driven Sign-to-Text systems.for Sustainable Accessibility in Deaf and Hard of Hearing Communities;generative Artificial Intelligence as a Tool to Design the Learning Process Using Active Learning Methodologies;Comparative Analysis of AI Chatbot Responses in a Computer-Aided Drawing Course;towards a Multi-agent Deep Reinforcement Learning Approach for End-to-End Latency Minimization in Complex Communication Networks;Natural Language Processing (NLP) for Hate Speech Detection in Vietnamese Language: Challenges and Implementation;Enhanced Lung Cancer Detection in CT Scans Using Deep Learning Architectures;evaluating Llama-3.1 for Adverse Drug Event Entity and Relationship Extraction Across Prompting Techniques;WayOutBench: Evaluating Multimodal LLMs in Interactive Environments;Enhancing Social Media Engagement Sentiment Prediction: A Random Forest and SMOTE-Based Approach with Explainable AI;using Kaldi for Phonetic Transcription: Evidence from the Corpus of Spoken Russian;A Non-sequentially Trained MLP Model for Financial Time Series Forecasting;cyberbullying Text Classification Using Neural Networks, Generative Models, and Graph Analysis;an Analytical Study of H-2 Visa Applications Acceptance Rates in the U.S.A.;a 3D Convolutional Neural Network for Real Time Car Crash Detection in Road Traffic Videos;comparative Analysis of Brain Tumor Classification Using Transfer Learning;analyzing Pedestrian and Bicycle Activity Patterns in Downtown Los Angeles Using Python;Automated Detection and Geolocation of Olive Tree Crowns in UAV Ima

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Cloud-Enhanced Transfer Learning Framework for Medical Image Analysis: Advancing Diagnostic Speed and Accuracy in Healthcare 3

Cloud-Enhanced Transfer Learning Framework for Medical Image...

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3rd international conference on Integrated Circuits and Communication systems. ICICACS 2025

作者： Prabu, S. Chandra, N. Subhash Bhavani, M. Varma, V. K. Chaitanya Soni, Mukesh Mahendra Institute of Technology Department of Electronics and Communication Engineering Namakkal India Cvr College of Engineering Department of Computer Science and Engineering Mangalpalle India Rajalakshmi Institute of Technology Department of Artificial Intelligence and Data Science Chennai India Sagi Rama Krishnam Raju Engineering College Department of Mechanical Engineering Bhimavaram India Dr. D. Y. Patil Vidyapeeth Dr. D. Y. Patil School of Science & Technology Pune India

ISBN: (纸本)9798331508456

When it comes to medical image analysis, problems arise due to the scarce amount of data and computational resources in medical environments. This is because, as earlier stated, cloud settings demand efficient models capable of delivering more reliable diagnostic results without straining the cloud's computing resources. In this work, we presented a transfer learning based on DenseNet-201 as well ResNet-152 architectures with a new large dataset containing 15,000 medical images of different modality. By utilizing the distributed cloud computing and hypermeters precision strategy, the proposed model was found to have 95.8 % of accuracy, 94.2% sensitivity, and 96.3%specificity. It also reduced the processing time by sixty-eight percent over standard methods across the facilities. Five different datasets validated the proposed approach, achieving an external accuracy of 92.4%, indicating improved generalization performance. The enhancement of accuracy to approximately 90% and the reduction in required computation demonstrate its feasibility for extensive clinical applications on the cloud, spanning across hospitals. © 2025 IEEE.

关键词： distributed cloud

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3rd international conference on computing and Communication Networks, ICCCN 2023

3rd International Conference on Computing and Communication ...

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3rd international conference on computing and Communication Networks, ICCCN 2023

ISBN: (纸本)9789819726707

The proceedings contain 60 papers. The special focus in this conference is on computing and Communication Networks. The topics include: Enhancing Security in Wireless Sensor Networks: A Broadcast/Multicast Authentication Framework with Identity-Based Signature Schemes;TSFTO: A Two-Stage Fuzzy-Based Tasks Orchestration Algorithm for Edge and Fog computing Environments;tracking Climatic Variations Through Smart IoT-Driven Approach: An Exploratory Analysis;Design and Manufacturing of an Efficient Low-Cost Fire Surveillance System Based on GSM Communications and IoT Technology;a Comparative Analysis of Optimized Routing Protocols for High-Performance Mobile Ad Hoc Networks;integrating Sandpiper Optimization Algorithm and Secure Aware Routing Protocol for Efficient Cluster Head Selection in Wireless Sensor Networks;the Effects of Weather Conditions on Data Transmission in Free Space for Wireless Sensor Networks;Using Wireless Sensor Network Performance and Optimizing in Underground Mines with Virtual MIMO Antenna;a Novel Logistic Regression-Based Fire Detection Model Using IoT in Underground Coal Mines;An MQTT IoT Intrusion Detection System Using Deep-Learning;multi-objective Optimal Feature Selection for Cyber Security Integrated with Deep Learning;application of Gradient Boosting Classifier-Based Computational Intelligence to Detect Drug Addiction Threat in Society;insurance 4.0: Smart Insurance Technologies and Challenges Ahead;review on Vision Transformer for Satellite Image Classification;primitive Roots and Euler Totient Function-Based Progressive Visual Cryptography;approach for Fire Detection Using Image Processing;review of Various Approaches for Authorship Identification in Digital Forensics;machine Learning Model for Traffic Prediction and Pattern Extraction in High-Speed Optical Networks;improved Markov Decision Process in Wireless Sensor Network for Optimal Energy Consumption.

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3rd IEEE international conference on distributed computing and Electrical Circuits and Electronics, ICDCECE 2024

3rd IEEE International Conference on Distributed Computing a...

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3rd IEEE international conference on distributed computing and Electrical Circuits and Electronics, ICDCECE 2024

ISBN: (纸本)9798350318609

The proceedings contain 299 papers. The topics discussed include: time series modelling approach for predictive analytics;research on the recognition of accounting information distortion by random forest algorithm;reconstruction and update of 3D model of mechanical products based on 3D point cloud data;prediction of soil organic carbon content using machine learning based fuzzy C-means clustering;fault detection and classification in power transmission lines using discrete wavelet transform-based swish recurrent neural network;immersive dramatic space 3D layout using panoramic image reconstruction algorithm;multi-objective optimization of noise in a high-speed railway by a hybrid algorithm;new energy vehicle customer mining model based on machine learning algorithm;and robotization of agriculture using image processing techniques.

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