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Deep learning and machine Vision based Robot for Fire Detection and Control 4

Deep Learning and Machine Vision based Robot for Fire Detect...

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4th international conference on Inventive Research in Computing Applications, ICIRCA 2022

作者： Tephila, M.Benedict Aswini, P.M. Abhinandhan, S. Arjun, K.K. Sri Krishna College of Engineering and Technology Department of Ece Coimbatore India

ISBN: (数字)9781665497077

ISBN: (纸本)9781665497077

Robotics and deep learning algorithms have emerged as a crucial part of our everyday life. Most of the recent image recognition innovations use deep learning, big data analysis, and artificial intelligence as their core platform. Hence in this work, a firefighting robot that uses deep learning is introduced to detect fire. On detection, the type of fire is also identified with the help of a combination of Imagenet and Alexnet. A Raspberry Pi is used to execute the proposed work and is programmed to function efficiently to detect and classify fire. Based on the results obtained, it is concluded that classification accuracy stands at 92%, while the detection of fire is accurate up to 97.75%. the proposed work shows a dynamic improvement in the accuracy of detecting fire with the help of robots and further classifying them using machine vision. © 2022 IEEE.

关键词： Fires

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Analysis Influencing Factors of Consumer Satisfaction of Men's Sweaters Based on Online Reviews 4

Analysis Influencing Factors of Consumer Satisfaction of Men...

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4th international conference on Applied machine learning, ICAML 2022

作者： Shi, Wenqi Cheng, Fan School of Fashion ShaanXi Institute of International Trade & Commerce Xi'an China Silk Road Research Center of Cultural and Creative Industry ShaanXi Institute of International Trade & Commerce Xi'an China

ISBN: (纸本)9781665462655

In order to explore the main factors influencing the satisfaction of online shopping consumers of men's woolen sweaters. the binary Logistic model was used to conduct data mining and analysis of online comments on JD. the results showed that the factors influencing customer satisfaction include the intrinsic quality of woolen sweaters, marketing strategy, logistics and customer service, a total of 12 factors. Among them, the product's perceived experience, fabric, technology, style, color, brand, price, activity, delivery speed and pre-sale service have a significant positive impact on satisfaction. Consumers are more satisfied with the perceived experience and style, but less satisfied with the brand and after-sale service. © 2022 IEEE.

关键词： Customer satisfaction

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Classification of Inflammatory Gene Expression patterns with machine learning Models

Classification of Inflammatory Gene Expression Patterns with...

引用

pattern recognition and machine learning (PRML), IEEE international conference on

作者： Yeonglong Ay Yit Hong Choo Asim Bhatti Chee Peng Lim Department of Neurology and Neurological Science Stanford University Stanford U.S.A Institute for Intelligent Systems Research and Innovation Deakin University Geelong Australia

Dementia is a complex neurological disorder characterized by a progressive decline in cognitive functions. Recent studies have suggested a link between neuroinflammation and the development of dementia, particularly in Alzheimer’s disease. this study focuses on the analysis of inflammatory gene expression patterns in the parietal cortex (PCx) and temporal cortex (TCx) from a human brain RNA sequence data set, aiming to derive insights into the underlying genetic link associated with dementia, as well as prediction of dementia. Using five machine learning and statistical methods, our study reveals better detection and classification of dementia patients using PCx-related gene patterns, as compared with those from the TCx. Our findings support the hypothesis that the PCx plays a significant role in neuroinflammatory responses associated with dementia. Based on this preliminary study, machine learning models offer a useful approach to recognize inflammatory gene expression patterns and providing a valuable biomarker analysis and prediction for dementia diagnosis.

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Pallet Detection and 3D Pose Estimation via Geometric Cues Learned from Synthetic data 4th

Pallet Detection and 3D Pose Estimation via Geometric Cues...

引用

4th international conference on pattern recognition and Artificial Intelligence, ICPRAI 2024

作者： Beleznai, Csaba Reisinger, Lukas Pointner, Wolfgang Murschitz, Markus Assistive & Autonomous Systems AIT Austrian Institute of Technology Vienna Austria AGILOX Services GmbH Neukirchen bei Lambach Austria

ISBN: (纸本)9789819787043

Vision-based object recognition is an important enabler for automating specific workflows in production and transportation scenarios. Locating and manipulating pallets as common functional objects represents a relevant robotic task in these domains. However, learning accurate neural models to estimate the location and pose of such objects is non-trivial. the main complexity stems from the underlying diversity of representing pallet objects: varied viewing conditions, frequent occlusions, self-occluded parts, diverse pallet materials jointly span a vast space of possible appearances. We present a solution which tackles the data diversity problem and the issue of occlusions. On one hand, we demonstrate how to rely on synthetic image pairs to compute geometry-encoding stereo disparity images, highly independent from appearance variations and exhibiting a small synthetic-to-real data domain gap. On the other hand, we introduce a novel point- and line-segment-based voting scheme, yielding a strong support for object presence in case of occlusions and up to distances of 8 m. We provide a quantitative evaluation of recognition accuracy for several network architectures using a manually fine-annotated multi-warehouse data-set. Based on the presented pallet recognition scheme, we also describe an automated forklift demonstrator, able to perform automated pallet pick-up and drop-off operations under diverse observation conditions. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Stereo image processing

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machine learning-Based Music Recommendation System from Spotify 15th

Machine Learning-Based Music Recommendation System from Spo...

引用

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： Bahadure, Nilesh Bhaskarrao Patil, Prasenjeet D. Kalbande, Sanjula Pipalatkar, Shailaja Nagar, Somesh Kuhikar, Om Pune India MIT School of Engineering MIT ADT University Loni Kalbhor Pune India

ISBN: (纸本)9783031889912

Music plays a vital role in our lives. there is a huge amount of information available everywhere;our task is to filter out only the information that is relevant for users in which they are interested or which suits their goals. In this work, we are aiming to build a music recommendation system that will be content-based. A recommendation system is a filtering system that will predict the user’s choices in music based on their preferences. the content filtering method relies on the characteristics of data and filters it according to the same. So, we implemented a model that works well for a large number of instances and datasets. the design and implementation of the proposed song recommendation system are highly effective and consistently stable. the encouraging results, with an accuracy of 90.5%, provide a new idea and a theoretical basis and open a new avenue for future research on song recommendation systems. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： elbow method K-NN machine learning

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Sentiment Analysis of Tweets on Social Issues Using machine learning Approach 4

Sentiment Analysis of Tweets on Social Issues Using Machine ...

引用

4th international conference on Digital Age and Technological Advances for Sustainable Development, ICdata 2023

作者： Bellar, Oumaima Baina, Amine Bellafkih, Mostafa National Institute of Posts and Telecommunications Inpt Raiss Team Strs Lab Rabat Morocco

ISBN: (纸本)9798350311112

Since the arrival of Web 2.0, there has been a growing interest in knowing the opinions of Internet users who express themselves spontaneously and in real time. this mass of opinion data is accessible with web mining tools, with a constantly renewed collection of information. Sites have specialized in collecting these opinions in certain fields (movie reviews, for example), and Internet users have become accustomed to consulting the opinions and ratings submitted by others as soon as they have to make a purchasing decision for a technical product, or even for a hotel reservation. Opinions are therefore of interest to Internet users and have given rise to multiple applications and services, which creates a virtuous circle of encouragement to give one's opinion and even to be recognized as giving relevant opinions and followed by others. But this data is also of interest to brands and research firms who are trying to understand this 'aggregated crowd sentiment'. Often sensitive to the 'your reputation can be destroyed because of a blog comment' fantasy, brands are concerned about their online identity but also seek to better understand the expectations and criticisms that Internet users have of them. Hence the growing development of techniques to capture these evaluations from Internet users, ranging from the simple counting of positive or negative comments to a more detailed analysis of the content of these comments. the purpose of this document is to provide detailed steps in the process of analyzing sentiments on a data using machine learning. © 2023 IEEE.

关键词： Sentiment analysis

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Research on preprocessing and feature extraction methods for handwriting images based on Gabor texture learning

Research on preprocessing and feature extraction methods for...

引用

pattern recognition and machine learning (PRML), IEEE international conference on

作者： Guzalnur Amrurla Nurbiya Yadikar Kurban Ubul Institute of Information Science and Engineering Xinjiang University Urumqi China

Abstract: Handwriting recognition is a science and technology that uses machines to analyze the differences in handwriting styles to determine the identity of the writer. In the fields of computer vision and pattern recognition, handwriting recognition technology has also received increasing attention and research from experts and scholars. At the same time, the Uyghur handwriting recognition technology is still in its early stages, and the research on Uyghur handwriting recognition methods is of great significance. In this paper, research work was mainly concened with off-line Uyghur handwriting identification method, with special attention is given basically in handwriting image preprocessing and feature extraction concerning special handwriting character structure using Gabor transform method. Main objective is to evaluate and achieves Uyghur handwriting identification related algorithms and techniques and promote automation of the process.

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Research on machine learning to reduce cost and increase efficiency in factories 4

Research on machine learning to reduce cost and increase eff...

引用

4th international conference on Big data Economy and Information Management, BDEIM 2023

作者： Zhang, Li Xie, Yuqiao Wu, Yuan Ran, Qian Zeng, Yuqing Tan, Xun Li, Hua HUBEICHINA TOBACCO INDUSTRY CO. LTD Hubei Enshi China

ISBN: (纸本)9798400716669

Since our country has proposed the goal of "reaching the peak of carbon, carbon neutral,"low-carbon reduction has become an inevitable trend. the construction and improvement of a carbon cost management system have become essential challenges that enterprises must face. For enterprises, integrating environmental considerations into their development strategy can not only address this challenge but also seize opportunities to enhance competitiveness. As major participants in the market economy and bearers of social responsibility, analyzing employees' low-carbon organizational behavior plays a crucial role in successfully implementing a low-carbon transformation strategy. In order to explore the application of data mining algorithm in enterprise cost reduction and efficiency increase, this study employs Support vector machine regression. the research involves collecting and processing business dining records along with relevant climatic data encompassing average temperature, weather conditions, maximum and minimum temperatures, and wind speed. data harmonization and onehot coding were performed on the collected data. Subsequent to data preprocessing, Pearson correlation analyses were performed on the corporate dining records and climate data. then, a prediction model based on Support vector machine regression models, incorporating techniques such as regularization and kernel functions to amplify prediction efficacy. the experimental outcomes underscore Support vector machine regression algorithms demonstrate feasibility and reliability. this study aims to help factories rationalize dining resources and improve dining experience. © 2023 ACM.

关键词： Support vector regression

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Assessment and Prediction of Corrosion Rate of Marine Railway Bridges Based on Ridge Regression Model

Assessment and Prediction of Corrosion Rate of Marine Railwa...

引用

pattern recognition and machine learning (PRML), IEEE international conference on

作者： Huan Wang Zhengbin Chen Rail Transit Branch of Sinohydro 7th Engineering Bureau Co. LTD Chengdu China

this investigation employs ridge regression analysis to assess and forecast the corrosion rate of maritime railway bridges. We have gathered and organized pertinent data, devising a regression model encompassing multiple attributes, intending to scrutinize seawater’s influence on railway bridge corrosion. the model’s performance is appraised using cross-validation techniques, and the significance of each point is measured via ridge regression coefficients. Experimental findings demonstrate that the ridge regression model excels in predicting the corrosion rate of maritime railway bridges, exhibiting minimal discrepancies between predicted and actual values. Upon analysis of the model’s attributes, we discern that salinity and sulfide content in seawater are critical determinants of railway bridge corrosion rates. the findings of this study provide valuable reference points for marine engineering and railway bridge construction while offering novel insights into the application of ridge regression models for predicting and analyzing maritime environmental issues.

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Encrypted Transmission Method of Network Speech recognition Information Based on Big data Analysis 1

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4th international conference on machine learning for Cyber Security, ML4CS 2022

作者： Zhang, Yanning Beijing Polytechnic Beijing100016 China

ISBN: (数字)9783031200960

ISBN: (纸本)9783031200953

Voice is the medium of language. With the development and popularization of network technology, voice has also become the main carrier of network information. Because the network is open to a certain extent, it poses a great threat to the security of network information transmission. therefore, a research on encrypted transmission method of network speech recognition information based on big data analysis is proposed. Preprocess network speech signals (sampling, quantization, filtering, pre emphasis, windowing and framing, endpoint detection, etc.), extract network speech signal features based on big data analysis technology, apply hidden Markov model to obtain network speech recognition information, build information encryption model PKI, effectively combine symmetric encryption algorithm and asymmetric encryption algorithm, and formulate encryption and decryption steps of speech recognition information. thus, the encrypted transmission of network speech recognition information is realized. the experimental data show that the minimum value of the network speech recognition information acquisition time of the proposed method is 10.09s, and the maximum proportion of successful speech recognition information encryption is 97%, which fully proves that the proposed method has better information encryption transmission effect. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cryptography

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