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检索条件"任意字段=3rd International Conference on Pattern Recognition and Machine Intelligence"

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Weather Image recognition Based on Convolutional Neural Network and Transfer Learning 24

Weather Image Recognition Based on Convolutional Neural Netw...

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3rd international conference on Cryptography, Network Security and Communication Technology (CNSCT)

作者： Gao, Zunhai Qiu, Yuzhan Nanchang Inst Sci & Technol Sch Informat & Artificial Intelligence Nanchang Jiangxi Peoples R China Wuhan Polytech Univ Sch Math & Comp Sci Wuhan Peoples R China

ISBN: (纸本)9798400716959

This article analyzes the image features of various weather phenomena, collects and constructs a weather image dataset, and builds a convolutional neural network model based on deep learning methods for weather phenomenon recognition. Firstly, this article constructs a dataset of five common weather types, including sunny, rainy, snowy, foggy, and thunderstorm weather, which includes multiple weather types and is closer to real production and living conditions. Each category has 10000 annotated weather images. Secondly, in response to some issues with existing weather image classification methods, such as low recognition accuracy and slow model training speed, a ResNet50 based transfer learning model was constructed by introducing transfer learning on the basis of convolutional neural networks. This model has higher classification accuracy and faster recognition speed compared to traditional image recognition methods.

关键词： Weather recognition Convolutional neural networks Transfer learning ResNet50 network

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Vehicle Theft Detection Using Neural pattern recognition 3

Vehicle Theft Detection Using Neural Pattern Recognition

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3rd international conference on Pervasive Computing and Social Networking, ICPCSN 2023

作者： Jane Rubel Angelina, J. Subhashini, S.J. Kumar Rapuri, Anil Ravva, Vennela Rasala, Raghavendra Ray Adurgam, Sai Dcepak Kalasalingam Academy of Research and Education Dept of Computer Science and Engineering TamilNadu Krishnankoil India SRM Madurai College for Engineering and Technology Dept of Computer Science and Engineering TamilNadu Sivagangai India

ISBN: (纸本)9798350322842

Finding stolen cars is becoming increasingly important in many urban regions. An automated system for scanning license plates can recognize vehicle numbers without the need for human interaction. This work proposes a vehicle theft detection system based on neural pattern recognition, gaussian filter, and equilibrium optimization. The proposed architecture has significant speedup and higher accuracy rates. The proposed number plate recognition method has a maximum accuracy rate of 94% and an average reduction in the processing time of 32%. pattern recognition is the process of detecting regularities and patterns in data using machine learning. These analogies may now be uncovered via statistical analysis, historical data, or machine-generated knowledge. © 2023 IEEE.

关键词： Image segmentation

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Design of Piano Timbre recognition System Based on Computer Technology 3

Design of Piano Timbre Recognition System Based on Computer ...

引用

3rd IEEE international conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2024

作者： Li, Li Dalian Art College Liaoning Dalian116600 China

ISBN: (纸本)9798350380989

A set of piano tone recognition and electronic synthesis system suitable for modern Musical Instruments was established to better apply computer technology to the music industry. Firstly, the sound quality characteristic model of music works based on digital identification is proposed, and the overall structure and function of the system are analyzed. The sound quality identification and electronic synthesis system of piano are studied by using Boriet analysis. First of all, it must solve the problem of sound quality identification. Secondly, it uses digital identification technology to extract the multiplication points of piano sound from the characteristic matrix of piano sound color. In this way, the envelope which can reflect the evolution law of sound intensity with time is extracted, so as to improve the recognition effect of piano sound quality. Through the experimental and theoretical research, it is proved that the method can achieve high accuracy and SNR in the range of 6002100 Hz. The correct recognition rate of sound shows that the system has good perfection. © 2024 IEEE.

关键词： artificial intelligence intensity envelope curve Piano arrangement timbre feature extraction timbre recognition system

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Implementation of Face Feature Algorithms for Authentication of a Person (IFFAP) 3

Implementation of Face Feature Algorithms for Authentication...

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3rd IEEE international conference on Distributed Computing and Electrical Circuits and Electronics, ICDCECE 2024

作者： Ramachandra, A.C. Monisha, B. Muralapur, Poorvika Vasupraneetha, H. Nitte Meenakshi Institute Of Technology Department Of Ece Bengaluru India

ISBN: (纸本)9798350318609

The present conventional digital financial transaction at Automated Teller machines (ATM) is secured with PIN number, with this there are chances of forgetting or misusing to overcome this with the increase in technology and various advancements in financial infrastructure, most of the bank customers prefer to use Automated Teller machines (ATM). To improve the security in such cases a new generation ATM machine which is based on face recognition technology is used. It also assists with changing passwords which increases privacy and security. The high-quality image has an important role in the recognition process. We propose Implementation of Face Feature Algorithms for Authentication of a Person (IFF AP) technique, an attempt to solve, The LBP algorithm and Haar Cascade techniques are employed for this process. This technology helps in increased security and avoids unauthorized transactions. This mutually benefits banking institutions and the customers. Leveraging existing algorithms, particularly those based on Local Binary pattern (LBP) and Haar Cascade, reveals a commendable qualitative analysis showcasing high accuracy up to 92.85% and improves computational efficiency compared to existing Techniques. © 2024 IEEE.

关键词： Local binary pattern

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Survey on Classification of Skin Diseases Using machine Learning Techniques 3

Survey on Classification of Skin Diseases Using Machine Lear...

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3rd international conference on Power Electronics and IoT Applications in Renewable Energy and its Control, PARC 2024

作者： Nirupama Virupakshappa Sharnbasva University KLB Department of Artificial Intelligence and Machine Learning Kalaburagi India Sharnbasva University KLB Department of Computer Science and Engineering Kalaburagi India

ISBN: (纸本)9798350309409

Skin is our body's most important organ;skin disorders are currently a common and serious problem due to patients' sensitive skin, as well as physical and psychological consequences. Skin disease symptoms might differ greatly from person to person and may be permanent or temporary, severe or painless. Skin disease symptoms include clogging, inflammation, rashes, irritation, and other changes in skin appearance. Early detection of skin disorders is ideal because it reduces the patient's actual expenses while additionally preventing illnesses from developing and spreading. In recent years, Artificial intelligence (AI) has been used to diagnose skin disorders using machine learning algorithms and a large amount of different skin data stored in database. Recent studies on skin disease identification and classification using predictive algorithms, mechanisms, and specific systems resulted in higher accuracy. machine learning will play an important and promising role in real-time diagnosis of dermatological diseases in the future. © 2024 IEEE.

关键词： machine learning

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The Role of Artificial intelligence Applications in Developing the Quality of Teaching: A case study in Iraq 3

The Role of Artificial Intelligence Applications in Developi...

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3rd international conference on Computing and machine intelligence (ICMI)

作者： Hussein, Alaa Abdulkhaleq Univ Baghdad Coll Islamic Sci Baghdad Iraq

ISBN: (纸本)9798350372977;9798350372984

The current research aims to conduct an examination of the evolution of diplomacy form, from its traditional version into the electronic one, as well to assess its impact on the realm of international relations. the data used to reach the research aim is The U. S. State Department's tweets, which were posted in the Arabic Spring. This data analyzed qualitatively by selected five case studies, that highlight the impact of digital diplomacy on international relations, drawn from various regions of the Middle east and diplomatic contexts. the result explored that The U. S. State Department's Twitter Posts used to reflect values of freedom, democracy, and human rights, as well examining people sentiment changes over time. while they are downplaying or excluding references, to underlying US interests or power dynamics within conflict regions. at the end, the research concludes the significant impact of e-diplomatic that represented in the content of digital messaging which can have their effect on various aspects of international relations, including public opinion and foreign aid provision. This modern form of diplomacy harnesses the power of the Internet and digital platforms to conduct diplomatic activities, including communication, negotiation, and the dissemination of information.

关键词： AI quality of teaching services Arabic language teachers

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3rd IEEE international conference on Artificial intelligence, ICAI 2023

3rd IEEE International Conference on Artificial Intelligence...

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3rd IEEE international conference on Artificial intelligence, ICAI 2023

ISBN: (纸本)9798350322125

The proceedings contain 41 papers. The topics discussed include: diagnosing spinal abnormalities using machine learning: a data-driven approach;humor detection in English-Urdu code-mixed language;machine learning based fault classification using stray flux and stator current in induction motor;human robot interaction: identifying resembling emotions using dynamic body gestures of robot;a cybersecurity risk assessment of electric vehicle mobile applications: findings and recommendations;machine learning based human recognition via robust features from audio signals;imitation learning for autonomous driving cars;an efficient ensemble approach for fake reviews detection;intelligent system for the diagnosis of schizophrenia featuring brain textures from EEG;adversarial attacks on aerial imagery : the state-of-the-art and perspective;fake news detection using machine learning;real-time object detection and 3D scene perception in self-driving cars;and the next generation of cloud security through hypervisor-based virtual machine introspection.

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Capturing the Essence: Exploring Cutting-Edge Feature Extraction Methods in Digital Image Processing 3

Capturing the Essence: Exploring Cutting-Edge Feature Extrac...

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3rd IEEE international conference on Mobile Networks and Wireless Communications, ICMNWC 2023

作者： Prabu, S. Natarajan, B. George, Roshan Sujitha, S. Bharathi, P Divya Rajeswari, S. School of Computer Science and Engineering VIT University Chennai India Amrita Vishwa Vidyapeetham Chennai India Roever Engineering College Department of Computer Science and Engineering Tamilnadu India Panimalar Engineering College Department of Artificial Intelligence & Data Science Chennai India K. Ramakrishnan College of Engineering Department of Computer Science and Engineering Tamilnadu Tiruchirappalli India

ISBN: (纸本)9798350317022

Feature Extraction (FE) plays a vital role in the fields of image processing, machine learning and pattern recognition. Binarization, resizing, thresholding and normalization are the initial steps applied before extracting features from an image. FE methods are applied to images to extract the most essential features that help in detection, recognition and classification tasks. FE techniques are used in numerous applications, such as object recognition, character recognition and pattern recognition. This research study presents a comprehensive research study of different image FE techniques, including SURF, BRISK, PCA and SIFT, which have been employed for various applications in recent times. This research study explains each method's fundamental concepts and pros and cons and demonstrates in what scenario which feature extraction technique will be better. This research work also presents a summary table of FE techniques used in various applications with their accuracy percentage. © 2023 IEEE.

关键词： Edge Detection Feature Extraction Feature Selection Image Processing Image Representation

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2024 3rd international conference on Artificial intelligence, Internet of Things and Cloud Computing Technology, AIoTC 2024

2024 3rd International Conference on Artificial Intelligence...

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3rd international conference on Artificial intelligence, Internet of Things and Cloud Computing Technology, AIoTC 2024

ISBN: (纸本)9798331530280

The proceedings contain 81 papers. The topics discussed include: research on distributed computing power scheduling based on ant path optimization;facial expression recognition in museum settings using an enhanced residual networks;LSD3K: a benchmark for smoke removal from laparoscopic surgery images;enhancing single image de-raining with a sparse spatial transformer;research on image recognition and intelligent management of accounting bills based on information technology;cloud-based flight test data management and application platform;design and simulation of biped robot based on ball screw;thinking about anti-drone strategies;RGembed: a knowledge graph embedding model integrating dual-prediction and graph attention networks;and improving the CodeGeeX model based on the relative convolutional multi-head attention method.

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Mitigation of User-Prompt Bias in Large Language Models: A Natural Langauge Processing and Deep Learning Based Framework 3

Mitigation of User-Prompt Bias in Large Language Models: A N...

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3rd international conference on Computing and machine intelligence (ICMI)

作者： Tiku, Sarvesh Front Range Community Coll Dept Comp Sci & Informat Technol Boulder CO 80501 USA

ISBN: (纸本)9798350372977;9798350372984

The advent of large language models has opened new frontiers in the field of automated text generation, enabling more refined engagement with complex language-based tasks. Concurrently, this advancement has revealed a potential vulnerability: the inadvertent amplification of biases from user prompts, which may lead to the reinforcement of detrimental stereotypes and misinformation by these large language models. Addressing this multifaceted challenge, this paper delineates a framework that integrates natural language processing and deep learning, designed to detect, and neutralize bias in user prompts in real time. The core of this system is a carefully formulated algorithm, the result of rigorous training, validation, and testing on the CrowS-Pairs dataset, specifically aimed at measuring the degree to which U.S. stereotypical biases are present in language models. The framework achieved an accuracy of 93% and an F1-Score of 0.92 in pinpointing and alleviating biases.

关键词： Artificial intelligence Deep Learning Natural Language Processing Bias Detection Mitigation Computational Linguistics Predictive Modeling Bidirectional Encoder Representations from Transformers (BERT) Robustly Optimized BERT Approach

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