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检索条件"任意字段=Proceedings of the 3rd International Conference on Control and Computer Vision"

共 18817 条记录，以下是4481-4490 订阅

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Human Activity Recognition Using Conv-LSTM with Infrared Camera Surveillance

Human Activity Recognition Using Conv-LSTM with Infrared Cam...

引用

Advancement in Computation & computer Technologies (InCACCT), international conference on

作者： Bindu Madhavi Tummala Chitturi Purna Chandra Sekhar Andra Karthik Anupam Gupta Department of Computer Science and Engineering Velagapudi Ramakrishna Siddhartha Engineering College Vijayawada Andhra Pradesh India

ISBN: (数字)9798331543891

ISBN: (纸本)9798331543907

Human Activity Recognition (HAR) the usage of infrared (IR) video statistics leverages superior computer vision and deep gaining knowledge of techniques to detect and classify human activities in numerous environments, even beneath low or no-light situations. This is important for packages including safety, surveillance, and healthcare diagnostics. Deep mastering models, which includes convolutional neural networks (CNNs) and long short-term memory (LSTM) networks, play a substantial position in this technique. CNNs extract spatial features from person frames, while LSTMs model time-structured video sequences, permitting the accurate popularity of complex activities. In this have a look at, the Conv-LSTM version demonstrated superior performance, accomplishing an accuracy of ninety seven.71% on an infrared video dataset. This method outperformed other trendy models, consisting of Enhanced YOLOv5, Attention-primarily based LSTM, Deep Conv-LSTM, and movement recognition models based totally on thermal motion pictures. These outcomes highlight the effectiveness of the Conv-LSTM framework in infrared-based activity popularity, showcasing its potential for actual-time analytics in hard environments.

关键词： YOLO Accuracy Surveillance Computational modeling Video sequences Feature extraction Safety Human activity recognition Convolutional neural networks Long short term memory

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Smart System To Monitor and control Transformer Health Condition in Sub-Station

Smart System To Monitor and Control Transformer Health Condi...

引用

international conference on Robotics,Electrical and Signal Processing Techniques (ICREST)

作者： Sagor Dash Sanjoy Das MD. Baki Billah Balaram Das Istiaque Ahamed Abir Ahmed Department of Computer Engineering (CoE) American International University - Bangladesh (AIUB) Dhaka Bangladesh Department of Electrical and Electronics Engineering (EEE) American International University - Bangladesh (AIUB) Dhaka Bangladesh

A substation is the most important component of transporting or distributing electricity in any region or industry. To control and monitor the substation, different automation structures are developed in our country and around the world. The proposed system is to develop an IoT-based smart solution for monitoring and controlling the transformer in a substation. The control unit serves as the hub for all the system equipment and activities. Using an ultrasonic sensor and the DHT11, this smart solution can monitor transformer oil and temperatures. When the temperature of the transformer climbs over the specified value, the cooling fan turns on and provides sufficient air to lower the temperature. The voltage and current sensors' collected data determine whether the circuit is open or closed. This eliminates the expense at the substation by minimizing operating costs. As a result, both observational and operational effectiveness will undoubtedly improve.

关键词： Temperature sensors Temperature measurement Substations Prototypes Switches Oil insulation Signal processing

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Intelligent Glasses for the Visually Impaired with Google Cloud API

Intelligent Glasses for the Visually Impaired with Google Cl...

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Pervasive Computing and Social Networking (ICPCSN), international conference on

作者： Netish V.P M.Vidhya Lakshmi Puli Venkatesh Kumar K.Durga Devi Puli Nitish Kumar Electronics and Communication Engineering SRM Institute of Science and Technology Chennai India Computer Science Engineering-Data Science St.Ann's College of Engineering and Technology Chirala India

Visually challenged people struggle in their day to day life. People face difficulty in identifying objects, reading and navigation. Canes help them to detect obstacles during traveling. The Idea of this research work is to develop an auxiliary device with sensors that could be connected to ordinary glasses. The Camera provided with the device continuously captures images from the real time environment. The Images are processed with Machine learning algorithms in google vision API. Proposed model informs the user about the obstacles they face during navigation and the travel route. The device can determine the obstacle in front of the user and notify the user about the danger. It also helps the user to read out a text from a label or a document. The API provides a speech based Interface. The user can use voice to activate the device and process the information. The device also interacts with the user through voice.

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Human Following Robot using Kinect in Embedded Platform 1

Human Following Robot using Kinect in Embedded Platform

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1st international conference on the Paradigm Shifts in Communication, Embedded Systems, Machine Learning and Signal Processing, PCEMS 2022

作者： Kapgate, Sachin Sahu, Pravin Das, Manisha Gupta, Deep Visvesvaraya National Institute of Technology Department of Electronics and Communication Engineering Nagpur440010 India

ISBN: (纸本)9781665459044

This paper presents an embedded robotic system using Kinect sensor technology that is utilized to detect an individual target and track its movement in the surrounding. The developed system integrates both the features of computer vision and embedded robotics simultaneously. In this paper, a skeleton-based tracking algorithm is used because tracking plays an important role in localization and mapping. This system uses a gesture-based recognition that relies on Microsoft Kinect XBox 360 instead of a standard touch-based control system that can be utilized as a stand-alone system or subsystem to integrate into a larger system. The Kinect sensor captures the 3-dimensional information of the surroundings and recognizes the human body by retrieving the depth information that does not require wearing any kind of intrusive sensors. Firstly, this robotic system follows an individual by detection of torso point that is required for steering and maintaining a fixed safe distance for localization and mapping and provides a robust and reliable system. The proposed system can be utilized in a wide variety of applications such as work assistants, luggage carrying carts, etc. © 2022 IEEE.

关键词： computer vision

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Adaptive Context and Trust Aware Access control Mechanism for Personal Health Record in Ubiquitous Environment

Adaptive Context and Trust Aware Access Control Mechanism fo...

引用

Smart Systems for applications in Electrical Sciences (ICSSES), international conference on

作者： G Jagadamba G Chayashree R Chethan Dept. of Computer Science and Engineering Ramaiah University of Applied Sciences Bengaluru Karnataka Dept. of Infromation Sceince and Engineeing Vidya Vardaka College of Engineering Mysuru Karnataka Dept. of Mathemetics Siddaganaga Institute of Technology Tumakuru Karnataka

ISBN: (数字)9798331507671

ISBN: (纸本)9798331507688

In the ubiquitous world, Personal health record (PHR) is shared with authorized entity in a patient-centric health records exchange model. However, due to privacy concerns, access control over PHR is achieved through authentication techniques. But, scalability, flexible access, context-aware and efficient user withdrawal have remained the most significant challenges for control over the PHR data access. In this paper, a health record access framework is proposed for PHR access. The adoption of context based three-factor authentication techniques achieves scalable and fine-grained PHR access control. The proposed scheme allows dynamic variation of access policies to support efficient on-demand access under non-emergency and emergency scenarios.

关键词： Access control Privacy Adaptive systems Scalability Authentication Smart systems

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Automated Seismic Horizon Picking Using vision Transformer

Automated Seismic Horizon Picking Using Vision Transformer

引用

Artificial Intelligence and Software Engineering (ICAISE), international conference on

作者： John Oluwadamilola Olutoki Numair Ahmed Siddiqui Mohamed Elsaadany Maman Hermena Oluwaseun Daniel Akinyemi Zhaoyang Zhao Baskaran Venkateshwaran Department of Geoscience Center of Excellence in Seismic Imaging and Hydrocarbon Prediction Universiti Teknologi Petronas Bandar Seri Iskandar Perak Malaysia Department of Geoscience Universiti Teknologi Petronas Bandar Seri Iskandar Perak Malaysia Department of Earth and Atmospheric Science University of Houston Bandar Seri Iskandar Perak Malaysia State Key Laboratory of Petroleum and Resources and Prospecting CNPC Key Laboratory of Geophysical Exploration College of geophysics China University of Petroleum Beijing Beijing Changping District China

ISBN: (数字)9798331532864

ISBN: (纸本)9798331532871

Horizon picking is essential in seismic interpretation due to its impact on subsequent processes. Traditional manual and automatic methods are time-consuming and dependent on human expertise. Recently, deep learning techniques have been adopted to overcome these issues. Traditional convolutional neural networks (CNNs) have difficulty effectively capturing global features and complex spatial relationships in seismic data. An architecture based on the self-attention mechanism called vision transformers has recently been introduced to overcome this challenge. In this study vision transformers were used to investigate its potential for picking horizons on seismic data for effective subsurface characterization. We established a training method for a vision Transformer (ViT) model grounded in structural geological modelling. This approach allows for the rapid and accurate mapping of horizon labels using structural modelling techniques. The findings indicated that vision transformer potential to horizons with a high level of accuracy and surpass traditional approaches' limitations.

关键词： Training computer vision Accuracy Three-dimensional displays Geology Manuals Learning (artificial intelligence) Transformers Reflection Software engineering

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DenseNet-SALD: A Lightweight Diseases and Pests Spatial Attention Classification Model

DenseNet-SALD: A Lightweight Diseases and Pests Spatial Atte...

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Software Engineering and Artificial Intelligence (SEAI), IEEE international conference on

作者： Zhanghao Qin Longqiu Chen Yanan Wang College of Artificial Intelligence and Computer Science Jiang Nan University Wuxi China College of Computer and Information Engineering Tianjin Agricultural University Tianjin China College of Science Tianjin University of Commerce Tianjin China

Leaf diseases and pests significantly impact crop yields, making it crucial to rapidly and accurately identify plant foliar diseases and implement appropriate control measures. We present a novel DenseNet-SALD-based model for identifying maize diseases and pests to improve classification performance. The proposed model was trained on a balanced dataset, incorporating an attention mechanism, Leaky ReLU activation function, and Dropout regularization to enhance its classification accuracy. The experimental results demonstrate that the proposed model outperforms conventional convolutional neural network models, such as DenseNet and AlexNet, achieving an accuracy of 99.0% and 85.03% for diseases and pests testing, respectively, meeting the primary pests recognition needs. This research provides valuable insights into the application of attention mechanisms in deep learning models for image recognition tasks, which could have potential implications for advancing the classification of corn leaf diseases and pests images.

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Research on Autonomous Berthing Algorithm of USV Based on Prior Berth Information

Research on Autonomous Berthing Algorithm of USV Based on Pr...

引用

international conference on Artificial Intelligence and computer Information Technology (AICIT)

作者： JieJie Kong Kang Yi Yuan Yi Zhao ZhengYu Li China Ship Development and Design Center WuHan China

ISBN: (数字)9798350365443

ISBN: (纸本)9798350365450

With the rapid development of unmanned equipment technology, in order to improve the autonomous navigation ability of USV s, this paper proposes an autonomous berthing algorithm for USVs with variable speed based on prior berth information, aiming at the autonomous berthing task of USVs in the complex environment of port and wharf. The algorithm can realize the autonomous departure from the docking dock under the low speed control. Considering the complexity of the dock environment, this paper combined Bezier curve to achieve multi-stage berthing path planning and splicing, and based on the parameter curve to achieve the smooth control of the USV under varying speed, to solve the problems of the USV in the berthing process such as too large Angle and bow output oscillation. By building an intelligent algorithm evolution verification platform combining virtual and real, and designing typical test scenarios, the process verification of autonomous berthing algorithm of USV was completed to verify the effectiveness and feasibility of the algorithm.

关键词： Splicing Buildings Velocity control Process control Boats Path planning Complexity theory Information technology Oscillators Autonomous robots

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Measurement of Muscle Stimulation and Hot Compression for Rehabilitation 3

Measurement of Muscle Stimulation and Hot Compression for Re...

引用

3rd international conference on Electrical, Communication and computer Engineering, ICECCE 2021

作者： Chirakanphaisarn, Neramitr Thongkanluang, Thadsanee Thammasat University Faculty of Engineering Department of Electrical and Computer Engineering Thailand Suratthani Rajabhat University Program in Materials Technology Manufacturing Faculty of Science and Technology Thailand

ISBN: (纸本)9781665438971

This research is to study the electric muscle stimulation system and hot compress. As well as focusing on building tools for applications in rehabilitation medicine and physical therapy. The neuromuscular system is an important mechanism in human life. In the event that the muscles are stressed or contracted while the subject is recovering, the need for recovery and stimulation tools is an important part of the physical therapy. We designed electrical circuits for automatic control and used an ArdUINO microcontroller to connect analog and digital ports to transmit and receive clinical parameters. The number of voluntary subjects was 20. Each subject remembered to perform 5 stimulation sessions for 10 minutes. Total period that the researcher collects data is approximately 3 months. The trials were based on ethical studies in humans, where trials and researches showed that subjects were 980% satisfied with very few side effects, and subjects had improved muscle development. © 2021 IEEE.

关键词： Muscle

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Accurate Modeling of CHP Plant by Digital Twin and Transformer Neural Network

Accurate Modeling of CHP Plant by Digital Twin and Transform...

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Digital Twins and Parallel Intelligence (DTPI), IEEE international conference on

作者： Guolian Hou Tianhao Zhang Zhiqiang Guo Ting Huang Qingwei Li School of Control and Computer Engineering North China Electric Power University Beijing China

This paper proposes an accurate modeling method for CHP plant by combining the digital twin(DT) and Transformer. Firstly, the actual operating data of the CHP plant is real-time affined to the simulation platform through DT. As Transformer has the advantages of strong robustness, parallel computing and wide applicability. It is used to establish the accurate model of supercritical CHP plant The innovation of this modeling method lies in the successfully combination of DT and Transformer, which has important reference value for promoting the flexible operation capacity of CHP plant. Finally, the effectiveness of the proposed model method is confirmed through the simulations on a 350 MW CHP plant.

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