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Proceeding of PRIS 2021 - 2021 3rd international conference on pattern recognition and Intelligent Systems

Proceeding of PRIS 2021 - 2021 3rd International Conference ...

引用

3rd international conference on pattern recognition and Intelligent Systems, PRIS 2021

ISBN: (纸本)9781450390392

The proceedings contain 19 papers. The topics discussed include: metric learning for context-aware recommender systems;food safety pre-warning system based on robust principal component analysis and improved Apriori algorithm;toward tracing the source of web attacks targeted at web applications;method of physical inventory checking on cigarette stereoscopic warehouse based on uav;improved correlation filter visual tracker by using scale estimation network;face anti-spoofing by using feature fusion;age estimation from facial images using transfer learning and k-fold cross-validation;synthetic aperture radar image target recognition based on hybrid attention mechanism;a deep learning model capable of producing heatmap probabilities for characters in natural scenes;and research on distortion correction of particleboard surface defect image.

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Energy-Efficient Monitoring of Industrial Processes Using IoT Sensors and Predictive Algorithms

Energy-Efficient Monitoring of Industrial Processes Using Io...

引用

Disruptive Technologies (ICDT), international conference on

作者： Gunjan Agarwal Arnav Kaushik Manoj Kumar Singh Vaishali Bhargava Saloni Bansal Department of Information Technology Raj Kumar Goel Institute of Technology Ghaziabad UP India Computer Science & Engineering Galgotia University Greater Noida UP India Computer Science & Engineering IMS Engineering College Ghaziabad UP India Department of Electrical Engineering GLA University Mathura UP India

ISBN: (数字)9798331519582

ISBN: (纸本)9798331519599

Industrial processes are becoming increasingly complex and larger in scale, which has resulted in a constantly growing demand for robust, scalable monitoring systems. Conventional monitoring strategies entail a huge quantity of sensors and steep infrastructure charges, main to excessive electricity intake and operational costs. Burkhard Theen, vice president at weather analytics company Iteris describes a smart monitoring device using IoT sensors and predictive algorithms for accurately tracking industrial processes on this track. The system is made using a low-voltage IoT sensor community at essential points within the process, which constantly collects and transmits statistics in real time. This data is then fed into the predictive algorithms that use machine learning techniques to analyze and determine any anomalies in the system. The system helps to improve process performance and reduce power consumption by identifying & addressing potential issues at their early stages.

关键词： Machine learning algorithms Power demand Electricity Companies Prediction algorithms Real-time systems Sensor systems pattern recognition Monitoring Intelligent sensors

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A Hybrid Deep Learning Model for Violence Detection

A Hybrid Deep Learning Model for Violence Detection

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Intelligent Data Communication Technologies and Internet of Things (IDCIoT), international conference on

作者： S Chandira Prabha S Kaviyadharshini A Annie Micheal Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527556

Current violence detection systems often face challenges such as high computational costs, real-time processing difficulties, and limited precision in detecting violent activities in dynamic environments. This research addresses these issues by proposing a hybrid deep learning model that integrates MobileNetV2 for efficient spatial feature extraction and ConvLSTM (Convolutional Long Short-Term Memory) for capturing temporal patterns. The model effectively discriminates between aggressive and non-aggressive behaviours in real-time video streams. Using the Kaggle Violence Dataset, which comprises 1,000 video clips of violent and non-violent activities, the system achieved an accuracy of 96%, showcasing its high performance. Additionally, an integrated alert system enhances practical application by sending real-time notifications via a Telegram bot, including details such as location, timestamp, and camera ID. This solution ensures timely responses to violent incidents, addressing the core issues of computational efficiency and real-time precision, while offering scalability and applicability in diverse scenarios.

关键词： Training Accuracy Computational modeling Streaming media Feature extraction Real-time systems Data models Computational efficiency pattern recognition Streams

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international conference on Artificial Intelligence and pattern recognition, AIPR 2014, Held at the 3rd World Congress on Computing and Information Technology, WCIT

International Conference on Artificial Intelligence and Patt...

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international conference on Artificial Intelligence and pattern recognition, AIPR 2014

The proceedings contain 25 papers. The topics discussed include: cloud and mobile security: challenges and future research directions;DLP-technologies: new directions and trends;using fuzzy logic to evaluate trust in e-commerce;gamification of teaching and learning activity: prospect and challenges of mobile game-based learning;ComboSplit: combining various splitting criteria for building a single decision tree;text classification using computational model of the cerebral cortex;restricted Boltzmann machines for modeling businesses;variables selection for multiclass SVM using the multiclass radius margin bound;on the enumeration of frequent patterns in sequences;predicting movie incomes using search engine query data;best-parameterized sigmoid ELM for benign and malignant breast cancer detection;inference engine for classification of expert systems using keyword extraction technique;comparison of classifiers for retinal pathology images using surf and bag-of-words model;content based video quality control for wide-area video surveillance systems;line detection by centre and width estimation;and interactive versus passive 2D face spoofing detection.

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3rd IAPR international conference on pattern recognition in Bioinformatics, PRIB 2008, Proceedings

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3rd IAPR international conference on pattern recognition in Bioinformatics, PRIB 2008

ISBN: (纸本)3540884343

The proceedings contain 39 papers. The topics discussed include: sequence based prediction of protein mutant stability and discrimination of thermophilic proteins;a method to find sequentially separated motifsin biological sequences (SSMBS);DFS based partial pathways in GA for protein structure prediction;evaluation of the stability of folding nucleus upon mutation;prediction of protein beta-sheets: dynamic programming versus grammatical approach;using multi-scale glide zoom window feature extraction approach to predict protein homo-oligomer types;extraction of binding sites in proteins by searching for similar local molecular surfaces;a clustering based hybrid system for mass spectrometry data analysis;a modified Markov clustering approach for protein sequence clustering;and domain-domain interaction identification with a feature selection approach.

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3rd international conference on pattern recognition Applications and Methods, ICPRAM 2014

3rd International Conference on Pattern Recognition Applicat...

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3rd international conference on pattern recognition Applications and Methods, ICPRAM 2014

ISBN: (纸本)9783319255293

The proceedings contain 18 papers. The special focus in this conference is on pattern recognition Applications and Methods. The topics include: Aggregation of biclustering solutions for ensemble approach;fuzzy c-means stereo segmentation;intra-class variance among multiple samples of the same person’s fingerprint in a cooperative user scenario;kernel matrix completion for learning nearly consensus support vector machines;an empirical comparison of support vector machines versus nearest neighbour methods for machine learning applications;improving the detection of relations between objects in an image using textual semantics;a TOF-aided approach to 3d mesh-based reconstruction of isometric surfaces;segmentation of tomatoes in open field images with shape and temporal constraints;fast and accurate pedestrian detection in a truck’s blind spot camera;comparing different labeling strategies in anomalous power consumptions detection;an efficient shape feature extraction, description and matching method using GPU;utilization of multiple sequence analyzers for bibliographic information extraction;statistically representative cloud of particles for crowd flow tracking;preserving maximum color contrast in generation of gray images and real-time facial analysis in still images and videos for gender and age estimation.

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Revolutionizing Legal Intelligence: advances in Neural Networks and Language Models for Legal NLP

Revolutionizing Legal Intelligence: Advances in Neural Netwo...

引用

international Symposium on Advanced Computing and Communication (ISACC)

作者： Raoul Samuel Noronha Alex Stanley Alenchery Deepa S Jayapriya J Vinay M Department of Computer Science Christ University Bengaluru India

ISBN: (数字)9798331523893

ISBN: (纸本)9798331523909

As the legal field continues to generate vast amounts of complex text, from contracts to court rulings, machine learning and natural language processing (NLP) techniques have emerged as valuable tools to help analyze and organize this data. In this paper, a number of state-of-the-art models will be reviewed and evaluated, including transformer models like BERT, GPT, and T5, and neural network models such as LSTM and CNN-RNN hybrids. These were then tested for the legal tasks of document classification, text summarization, and entity recognition. Some of the metrics used for evaluation include Accuracy, F1-Score, ROUGE, and BLEU. Advanced models, in particular large language models (LLMs), outperform the traditional methods by a large margin since they capture the niceties of legal language and structure much more completely. Meanwhile, high-quality legal datasets remain scarce, legalese remains incomprehensible to most, and the models are still relatively unexplainable. In sum, these challenges clearly call for future research in terms of data augmentation, explainable AI techniques, and more robust training methods that would allow AI-powered tools to be integrated much more effectively within lawyers’ workflows to support them in their decision-making processes.

关键词： Analytical models Law Large language models Neural networks Text summarization Transforms Transformers Data models Complexity theory Contracts

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3rd international Workshop on Computer Vision for Analysis of Underwater Imagery, CVAUI 2018, 7th international Workshop on Computational Forensics, IWCF 2018, and international Workshop on Multimedia Information Processing for Personality and Social Networks Analysis, MIPPSNA 2018 held at 24th international conference on pattern recognition, ICPR 2018

3rd International Workshop on Computer Vision for Analysis o...

引用

3rd international Workshop on Computer Vision for Analysis of Underwater Imagery, CVAUI 2018, 7th international Workshop on Computational Forensics, IWCF 2018, and international Workshop on Multimedia Information Processing for Personality and Social Networks Analysis, MIPPSNA 2018 held at 24th international conference on pattern recognition, ICPR 2018

ISBN: (纸本)9783030057916

The proceedings contain 16 papers. The special focus in this conference is on Computer Vision for Analysis of Underwater Imagery. The topics include: Categorization of Document Image Tampering Techniques and How to Identify Them;overview of the Multimedia Information Processing for Personality & Social Networks Analysis Contest;handwritten Texts for Personality Identification Using Convolutional Neural Networks;recognition of Apparent Personality Traits from Text and Handwritten Images;multimodal Database of Emotional Speech, Video and Gestures;from Text to Speech: A Multimodal Cross-Domain Approach for Deception Detection;marine Snow Removal Using a Fully Convolutional 3D Neural Network Combined with an Adaptive Median Filter;strategies for Tackling the Class Imbalance Problem in Marine Image Classification;an Online Platform for Underwater Image Quality Evaluation;tracking Sponge Size and Behaviour with Fixed Underwater Observatories;enhancement of Low-Lighting Underwater Images Using Dark Channel Prior and Fast Guided Filters;Underwater-GAN: Underwater Image Restoration via Conditional Generative Adversarial Network;single Image Plankton 3D Reconstruction from Extended Depth of Field Shadowgraph;a Novel Method for Race Determination of Human Skulls.

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Advancements in IoT and Sensor-Enabled Wearable Devices for Healthcare Applications

Advancements in IoT and Sensor-Enabled Wearable Devices for ...

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3rd IEEE international conference on Automation and Computation, AUTOCOM 2025

作者： Chowdhury, Srijit Kaur, Ashmeet Spoorthi, B. Prince, P. Grace Kanmani Agarwal, Trapty Vashisht, Nitish Centre for Cyber Security Odisha Bhubaneswar India Chitkara University Chitkara Centre for Research and Development Himachal Pradesh Baddi India Karnataka Bangalore India Sathyabama Institute of Science and Technology Department of Biomedical Engineering Tamil Nadu Chennai India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India

ISBN: (纸本)9798331542375

Technology has changed how healthcare is delivered- we now have the Internet of Things and sensor-enabled wearable devices today. These improvements have dramatically improved patient results by allowing actual pursuing then data analysis, translating to more customized health care being presented earlier. Linked strategies such as smart watches and suitability chasers have enabled medicinal professionals to access a patient's status remotely. These devices monitor energetic symbols, action stages, and sleeping patterns, provided actual alerts intended for early-stage recognition of fitness problems then chronic and chronic ailments remotely. Such technology facilitates uninterrupted patient-healthcare provider communication, ensuring prompt aid and better interaction. Furthermore, using AI and MI in these devices leads to better analytics for physicians' treatment options. Sensor-enabled wearable have reminded and tracked patients to better comply with treatment plans. This translates into tangible improvements in health and economic outcomes. The healthcare division has experienced an essential alteration owing to the evolution of the IOI and sensor-enabled wearable devices, bringing about better care to patients worldwide and moving one step towards predictive, personalized health. The possibilities these devices offer for changing healthcare are seemingly endless, and as technology gets more advanced, they will continue evolving. © 2025 IEEE.

关键词： pattern recognition

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3rd international conference on Recent Trends in Image Processing and pattern recognition, RTIP2R 2020

3rd International Conference on Recent Trends in Image Proce...

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3rd international conference on Recent Trends in Image Processing and pattern recognition, RTIP2R 2020

ISBN: (纸本)9789811604928

The proceedings contain 78 papers. The special focus in this conference is on Recent Trends in Image Processing and pattern recognition. The topics include: Ensemble of Nested Dichotomies for Author Identification System Using Similarity-Based Textual Features;Feature Combination of Pauli and H/A/Alpha Decomposition for Improved Oil Spill Detection Using SAR;a Fast and Efficient Convolutional Neural Network for Fruit recognition and Classification;copy-Move Image Forgery Detection Using Discrete Wavelet Transform;a Comprehensive Survey of Different Phases for Involuntary System for Face Emotion recognition;classification of Vehicle Type on Indian Road Scene Based on Deep Learning;indian Road Lanes Detection Based on Regression and clustering using Video Processing Techniques;detection of Emotion Intensity Using Face recognition;double Authentication System Based on Face Identification and Lipreading;fuzzy Approach to Evaluate Performance of Teaching Staff in Technical Institutions;safety Gear Check at Industries and Laboratories Using Convolutional Neural Network Based on Deep Learning;analysis of Changing Trends in Textual Data Representation;detection of Falsary Happening on Social Media Using Image Processing: Feature Extraction and Matching;Development of Multi Faces recognition System Using HOG Features and Neural Network Classifier in Real Time Environment;extraction of Key Frame from Random Videos Based On Discrete Cosine Transformation;Prediction of SO2 Air Pollution Quality Parameter of Kolhapur City Using Time Series Analysis;A Big Data Prediction for Weather Forecast Using Hybrid ARIMA-ANN Time Series Model;automatic Detection of Riots Using Deep Learning;protecting Big Data Sets from Unauthorized Users on Cloud;text Categorization: A Lazy Learning-Based Approach.

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