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Tea Bud Identification and Picking Location Using Improved Yolov7 Algorithm 3rd

Tea Bud Identification and Picking Location Using Improved Y...

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3rd international conference on Machine Learning, Cloud Computing and Intelligent Mining, MLCCIM 2024

作者： Liu, Hongwei Zhang, Jingui Yang, Yongjun Gong, Daoxiong Faculty of Information Technology Beijing University of Technology Beijing100124 China Agricultural Comprehensive Service Center Liangshi Tang Sub-District Office Shaodong City Hunan Shaoyang422800 China Hunan Tea Research Institute Hunan Academy of Agricultural Sciences Changsha410125 China

ISBN: (纸本)9789819624676

Tea is an important cash crop. Because the tea shoots in the tea garden are very similar to the old leaves, and the environment of tea buds in tea gardens is complicated, the difficulty of picking tea buds is increased. Aiming at the problems that tea buds are tough to identify and the picking points are challenging to locate in the complex environment in reality, this paper proposed a detection model based on Yolov7 for tea bud recognition and key point location. In this model, some conventional convolutional modules are changed to Diverse Branch Block (DBB), which can enrich the feature space and obtain more feature information of tea buds. The GE attention convolution module is incorporated to the neck network to boost the model's use of contextual features, so as to accurately locate the key point of the tea bud. The ELAN module is replaced by P-ELAN module, which reduces the redundant calculation and the size of the model. The outcomes of the experiment demonstrate that the mean Average Precision (mAP) of tea buds and their key points is increased by 3.81% in contrast to the original Yolov7. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Key point detection P-ELAN module Target detection tea buds picking

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Biometric Authentication with Blockchain: A Secure and User-Friendly Approach 3rd

Biometric Authentication with Blockchain: A Secure and User-...

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3rd international conference on Intelligent Systems and Sustainable Computing, ICISSC 2023

作者： Subburaj, T. Raju, K. Srujan Suthendran, K. Kumar, Kovuri Praveen Rekha, Ch. Sultana, Saba Deeraj, C. Department of Master of Computer Applications Rajarajeswari College of Engineering Bengaluru India Department of CSE CMR Technical Campus Telangana Hyderabad India Department of Information Technology Kalasalingam Academy of Research and Education Tamilnadu Krishnankoli India

ISBN: (纸本)9789819783540

"Biometric Authentication with Blockchain: A Secure and User-Friendly Approach" proposes a novel system, a Blockchain-based Distributed biometric Authentication System (BDAS), to address vulnerabilities in existing biometric authentication methods. The primary concerns tackled include the leakage of biometric information, irregularity in authentication modules, and non-transparency in information management. BDAS, leveraging blockchain technology, establishes a decentralized and distributed authentication system, ensuring reliable and secure authentication while minimizing performance overhead. The authors present a detailed exploration of biometric authentication, emphasizing the immutability of biometric data and the challenges associated with centralized management. They introduce BDAS as a solution that utilizes blockchain to enhance security, reliability, and transparency in biometric authentication. The paper includes an insightful evaluation of BDAS, comparing its performance with conventional authentication systems. The proposed system exhibits increased reliability in scenarios involving disabled clients, outperforming traditional systems. The authors conclude by highlighting BDAS's contributions to securing biometric information and propose future enhancements, such as optimizing template segmentation processes and considering the number of nodes for improved reliability. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Information leakage

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Research on Obstacle Detection Method of Rail Transit Based on Deep Learning 3rd

Research on Obstacle Detection Method of Rail Transit Based ...

引用

3rd international conference on Information Control, electrical engineering, and Rail Transit, ICEERT 2023

作者： Tao, Yun Xu, Yongneng Nanjing University of Science and Technology Jiangsu Nanjing210094 China

ISBN: (纸本)9789819788903

A lightweight obstacle detection model based on an improved YOLOv5s detection network is proposed to address the shortcomings of traditional train track obstacle detection methods, such as poor real-time performance and low detection accuracy for small targets. On the basis of introducing linear bottleneck and reverse residual structure, the backbone network, together with SE, forms a new network module MobileNetV3, which makes the model lighter without reducing the accuracy rate. Starting from the feature fusion of neck, a weighted bidirectional feature pyramid BiFPN is introduced to enhance the underlying information of feature maps, enabling information fusion of feature maps at different scales, thereby enhancing feature information. Adding CA spatial attention mechanism at the end of the model feature extraction network reduces the loss of important position information during the training process. The experimental results show that the improved model improves the detection accuracy by 1.2 percentage points compared to the original YOLOv5s algorithm on a self-made diversified rail transit dataset, while reducing the model size by 4.1 MB and increasing the detection speed by 7 FPS. It has certain feasibility and superiority in detecting track obstacles. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Information fusion

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A Comprehensive Sentiment Analysis on Beauty Product Usage Among Bangladeshi Comsumers 3rd

A Comprehensive Sentiment Analysis on Beauty Product Usage ...

引用

3rd international conference on Trends in Electronics and Health Informatics, TEHI 2023

作者： Jahan, Ishrat Jahan Mim, Sabiha Shahidur Rahman, Mohammad Computer Science and Engineering Shahjalal University of Science and Technology Sylhet3114 Bangladesh

ISBN: (纸本)9789819739363

Beauty products are an integral part of daily routines for many women. The beauty industry continually evolves, introducing innovative formulations and trends that cater to diverse preferences and needs. Sentiment analysis of beauty products is crucial as it allows companies to understand customer opinions, preferences, and experiences. In this study, we explore sentiment analysis in the context of beauty products. We collected data from various platforms like ***, ***, and ***, resulting in a dataset of 4431 reviews. Employing this unique dataset, we conducted a comprehensive analysis, employing a trio of neural network architectures: the foundational simple neural network, the robust 1D convolutional neural network (1D CNN), and the intricate long short-term memory (LSTM). Upon completing data preprocessing, we incorporated word embeddings derived from the GloVe 100D file, resulting in the attainment of an accuracy level of 78.78%. By combining data collection, model experimentation, and embedding techniques, we gain a multifaceted view, offering deeper insights into beauty product sentiment. In addition to advancing sentiment analysis methodologies, our study signifies a positive step toward empowering beauty industry stakeholders with actionable intelligence. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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Enhancing Grayscale Image Clarity Through Blind Deconvolution and PSF Estimation With Total Variation Regularization 3rd

Enhancing Grayscale Image Clarity Through Blind Deconvolutio...

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3rd international conference on Intelligent Systems and Sustainable Computing, ICISSC 2023

作者： Narasimharao, Jonnadula Kumar, Voruganti Naresh Kirankumar, Adepu Pooja, Bejjanki Rambabu, D. Joshi, Ganpat Department of CSE CMR Technical Campus Telangana Hyderabad India Sreenidhi Institute of Science and Technology Telangana Hyderabad India Department of Computer Science and Engineering Madhav University Rajasthan India

ISBN: (纸本)9789819783540

Nowadays, the usage of digital cameras in daily life has increased, leading to a growing demand for enhancing the quality of captured images. One of the most challenging problems in image processing is the restoration of blurred or out-of-focus images. This paper presents Enhancing grayscale image clarity through blind deconvolution and PSF estimation with total variation regularization. This blind deconvolution approach is used to handle the problem of removing blur from acquired photos, making it easier to restore defocused grayscale photographs. Determining the ideal picture and the point spread function (PSF) may be challenging when using blind deconvolution, which aims to recreate a clear ideal image from a single fuzzy image. As a result, this work also introduces a unique PSF estimate technique that makes use of an adaptive filter and total variation regularization. Finally, the results obtained after implementation are demonstrated based on the blur type and performance metrics, which include the mean square error and the peak signal-to-noise ratio. The experimental outcomes indicate that our method is the best among various other methods in terms of deblurring performance. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adaptive filtering

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3rd international conference on electrical, computer and Communication engineering, ECCE 2023

3rd International Conference on Electrical, Computer and Com...

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3rd international conference on electrical, computer and Communication engineering, ECCE 2023

ISBN: (纸本)9798350345360

The proceedings contain 137 papers. The topics discussed include: sexual harassment detection using machine learning and deep learning techniques for Bangla text;optimization strategies for micro-grid energy management and scheduling systems by sine cosine algorithm;efficient hardware and software co-design for EEG signal classification based on extreme learning machine;measurement and modeling of GaAs based nano-pHEMT: small signal to large signal analysis;Alzheimer’s disease classification from 2D MRI brain scans using convolutional neural networks;faulty classes prediction in object-oriented programming using composed Dagging technique;interpretable multi labeled Bengali toxic comments classification using deep learning;protein structure prediction in structural genomics without alignment using support vector machine with fuzzy logic;and impact of transmission line capacity expansion on electricity operation cost and selling price.

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Unlocking Personality Insights: Assessing Videos with Deep Learning Techniques 3rd

Unlocking Personality Insights: Assessing Videos with Deep L...

引用

3rd international conference on Signal and Data Processing, ICSDP 2023

作者： Athilakshmi, R. Jansi, R. Dutta, Indira Amulya Pavikars, M.M. Department of Computational Intelligence Faculty of Engineering and Technology SRM Institute of Science and Technology Tamil Nadu Kattankulathur603203 India Department of Electronics and Communication Engineering Faculty of Engineering and Technology SRM Institute of Science and Technology Tamil Nadu Kattankulathur603203 India

ISBN: (纸本)9789819795772

In contemporary times, monitoring criminal behavior and providing mental health therapy requires various activities related to an individual’s character. The development of an automated process for personality assessment through behavior analysis is still under research. Our contribution to this field involves combining deep learning with a regression-based machine learning model through a data pipeline for both audio and video data. We propose a comprehensive classification pipeline that utilizes supervised methods such as LSTM, GRU, and RNN, coupled with Visual Geometry Group (VGG) models for analyzing audio and visual data. The aim is to draw a comparative analysis between these methods to effectively analyze personalities. Our approach yields quality results, achieving an accuracy rate of 88.9% by combining VGG and NN for processing audio-visual data to analyze one’s personality composition. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Natural language processing systems

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2023 3rd international conference on electrical engineering and Mechatronics technology, ICEEMT 2023

2023 3rd International Conference on Electrical Engineering ...

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3rd international conference on electrical engineering and Mechatronics technology, ICEEMT 2023

ISBN: (纸本)9798350303698

The proceedings contain 172 papers. The topics discussed include: a novel distributed generation injection signal line fault detection technology;capacity estimation of lithium-ion batteries based on transformer model;park oriented energy event linkage management strategy;research on optimal scheduling of multi-source power system with complementary hydro and photovoltaic generation;integrated monitoring technology for tension and inclination of overhead transmission lines based on fiber Bragg grating;research on obstacle avoidance of a 7-DOF manipulator;insulator defect detection based on deep learning;stator modal analysis of permanent magnet motors for electric vehicles;study on fast stability of new power system based on the method of gradient dynamic deviation and PMU data;research on ADRC based on speed loop control of permanent magnet synchronous motor;and optimization design of flat wire permanent magnet synchronous motor for electric vehicles.

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Alertness Detection From Video Using Saccadic Velocity Profile 3rd

Alertness Detection From Video Using Saccadic Velocity Profi...

引用

3rd international conference on Signal and Data Processing, ICSDP 2023

作者： Panda, Nidhi Gupta, Supratim Kothapalli, Pujitha Department of Electrical Engineering National Institute of Technology Rourkela Odisha769008 India

ISBN: (纸本)9789819795772

The state of alertness plays a pivotal role in safety-critical operations, with reduced alertness posing risks to public health and safety. This paper focuses on measuring human alertness levels through non-intrusive, automatic, and cost-efficient means—specifically, utilizing distinctive facial features, such as saccadic eye movements. While current methods often rely on expensive proprietary eye trackers, our work explores the challenges and efficiency of employing a camera module for saccadic eye movement analysis. We trained a custom landmark detector to locate eye features, addressing localization challenges caused by low resolution and illumination variations. To enhance accuracy, we propose the use of a median filter to mitigate outlier effects. Additionally, we model an Extended Kalman Filter (EKF) to track eye coordinates, enabling the extraction of saccades and their velocity profiles. By mapping these profiles to Eigenspace, we successfully distinguish between alert and non-alert states. Experimental results demonstrate a classification efficiency exceeding 95% for the classification of states from saccadic velocity profiles. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Health risks

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The Scientific Analysis on Effective Yoga Posture Recognition Techniques 3rd

The Scientific Analysis on Effective Yoga Posture Recognitio...

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3rd international conference on Machine Vision and Augmented Intelligence, MAI 2023

作者： Rajgure, E.G. Patidar, Raghavendra School of Engineering ECE University of Technology Jaipur India

ISBN: (纸本)9789819743582

Today’s globalized scenario of competition has increased beyond expectations and to fulfill it, everyone has to face many competitive challenges and stressful work culture. In addition to prescribing the proper medication, many medical professionals advise optimal food, pranayama, and yoga to maintain this environment. Due to this physical health awareness number of professional yoga practitioners has been increased. Yoga exercises with proper postures are very important to get the benefits of increasing flexibility, muscle strength and also improve the functionality of the respiratory system. Along with spirituality, yoga has a number of impacts on the human body which ultimately integrates the coordination between mind and body. Due to which regular practitioners can maintain self-discipline and self-awareness. Due to improper methods of practice, maximum beginners do not get benefited from the routine yoga practice. Our main goal is to review the literature on yoga posture recognition systems based on scientific analysis. It also presents our methodical approach to posture recognition and classification based on AI and machine learning techniques, which we hope will help validate the accuracy of the postures performed during yoga practice. In order to collect time series data from sensors for various postures, our ongoing work will create an embedded wearable sensor-based system. Along with this, we have also enlisted measurable benefits of practicing yoga in the improvements of human health parameters. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Artificial intelligence Machine learning Posture recognition Yoga

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