检索结果-内蒙古大学图书馆

DeepRice: A deep learning and deep feature based classification of Rice leaf disease subtypes

Artificial Intelligence in Agriculture 2024年第1期11卷 34-49页

作者： P.Isaac Ritharson Kumudha Raimond X.Anitha Mary Jennifer Eunice Robert Andrew J Department of CSE Karunya Institute of Technology and Sciences CoimbatoreTamilnaduIndia Department of Robotics Engineering Karunya Institute of Technology and SciencesCoimbatoreIndia Department of Mechatronics Engineering Manipal Institute of TechnologyManipal Academy of Higher EducationManipalKarnataka 576104India Department of Computer Science and Engineering Manipal Institute of TechnologyManipal Academy of Higher EducationManipalKarnataka 576104India

Rice stands as a crucial staple food globally,with its enduring sustainability hinging on the prompt detection of rice leaf ***,efficiently detecting diseases when they have already occurred holds paramount importance for solving the cost of manual visual identification and chemical *** the recent past,the identification of leaf pathologies in crops predominantly relies on manual methods using specialized equipment,which proves to be time-consuming and *** study offers a remedy by harnessing Deep Learning(DL)and transfer learning techniques to accurately identify and classify rice leaf diseases.A comprehensive dataset comprising 5932 self-generated images of rice leaves was assembled along with the benchmark datasets,categorized into 9 classes irrespective of the extent of disease spread across the *** classes encompass diverse states including healthy leaves,mild and severe blight,mild and severe tungro,mild and severe blast,as well as mild and severe brown *** meticulous manual labelling and dataset segmentation,which was validated by horticulture experts,data augmentation strategies were implemented to amplify the number of *** datasets were subjected to evaluation using the proposed tailored Convolutional Neural Networks *** performance are scrutinized in conjunction with alternative transfer learning approaches like VGG16,Xception,ResNet50,DenseNet121,Inception ResnetV2,and Inception *** effectiveness of the proposed custom VGG16 model was gauged by its capacity to generalize to unseen images,yielding an exceptional accuracy of 99.94%,surpassing the benchmarks set by existing state-of-the-art ***,the layer wise feature extraction is also visualized as the interpretable AI.

关键词： Rice leaf disease Deep learning CNN Crop yield Agriculture Food security

来源：评论

学校读者我要写书评

暂无评论

Mimicking Muscle Relaxation Through 3D Print Materials & Magnetic Systems 19

Mimicking Muscle Relaxation Through 3D Print Materials & Mag...

引用

19th IEEE International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI, HONET 2022

作者： Roberts, Santana Voicu, Razvan Cristian Moghadam, Amir Ali Amiri Chang, Yusun Kennesaw State University Department of Robotics & Mechatronics Engineering AtlantaGA United States

ISBN: (纸本)9781665461979

The purpose of this study is to examine the inter-action of a magnetic system with that of an elastic 3D print design to replicate a muscle in contraction expanding back to its original relaxed state. An electromagnetic system uses a design made of soft material to maintain a compression length when an electric current is applied. When the current is removed, the system expands back to its original length due to the geometry and elastic properties of the material. Preliminary experiments on differing magnets help establish a separation distance between the magnets within the design. Mathematical models then further detailed the design using the cross-sectional area, length, and angle between supports to estimate deflection. This design was then tested using nonlinear simulations to displace the component at a distance equivalent to the estimated distance given from the calculations. The reaction force was then compared to the force in the calculations to estimate the percent difference. Once decent results were obtained, a model was 3D printed and tested to verify the findings. The secondary goals of this endeavor are to utilize common materials, reduce the complexity of production, and limit the number of components within the system to reduce failure points along with an estimated lower cost for the overall apparatus. © 2022 IEEE.

关键词： Muscle

来源：评论

学校读者我要写书评

暂无评论

Spectral and Morphological Classification of Celestial Objects using Physics Informed Machine Learning

Spectral and Morphological Classification of Celestial Objec...

引用

robotics, Automation, Artificial-intelligence and Internet-of-Things (RAAICON), 2019 IEEE International Conference on

作者： Md Fairuz Siddiquee Md Mehedi Hasan Department of Robotics and Mechatronics Engineering University of Dhaka Dhaka Bangladesh

ISBN: (数字)9798331534400

ISBN: (纸本)9798331534417

The classification of celestial objects has traditionally relied on spectral analysis, which involves identifying unique patterns in the light emitted or absorbed by the objects. In this study, we present a novel approach to categorizing celestial objects based on their spectral properties and morphological structures, leveraging physics-informed machine learning (PIML) techniques to enhance the classification accuracy and efficiency. In the spectral analysis, using Sloan Digital Sky Survey (SDSS) dataset, we classified stars, galaxies, and quasars, focusing on redshift and near-infrared values with i and z filters. Our analysis employed three machine learning models (K-Neighbors, SVM, Random Forest), and the performances were verified to be resilient applying hyperparameter tuning and cross-validation. The best-performing model, Random Forest Classifier, achieved 98% accuracy. In the morphological analysis, the YOLO v5 model was utilized on a customized dataset of astronomical images to further classify the Galaxy Class into five distinct categories and the YOLOv5 model detected those with an average precision of 92.6% and recall of 68.9%. In addition, the interpretability of the model is enhanced by the incorporation of physical knowledge, allowing astronomers to gain deeper insights into the underlying processes. Integrating physical knowledge into these ML models enhances interpretability, facilitating automated real-time analysis of big astronomical data and advancing our understanding of the cosmos.

关键词： YOLO Surveys Support vector machines Analytical models Accuracy Stars Spectral analysis Random forests Tuning Robots

来源：评论

学校读者我要写书评

暂无评论

AI-Driven 3D Printing: Generative Gcode for Quality and Efficiency

AI-Driven 3D Printing: Generative Gcode for Quality and Effi...

引用

IEEE Southeastcon

作者： Sean Haque Muhammad Hassan Tanveer Razvan Cristian Voicu Department of Robotics & Mechatronics Engineering Kennesaw State University Marietta Georgia

ISBN: (数字)9798331504847

ISBN: (纸本)9798331504854

Artificial Intelligence (AI) is transforming the landscape of three-dimensional (3D) printing by enabling generative approaches that extend beyond conventional, parameter-tuning strategies. Rather than merely adjusting nozzle temperatures or speeds, modern AI models can create or refine Gcode paths themselves, seeking to balance objectives such as print strength, dimensional accuracy, and defect minimization. This paper introduces a holistic AI-driven workflow for automated Gcode generation. We demonstrate that generative Large Language Models (LLMs) can parse, synthesize, and optimize printing instructions, thus offering an alternative to human-engineered slicing parameters. Our approach incorporates a continuous feedback loop in which a predictive model evaluates each generated Gcode script for potential print outcomes. Experimental results illustrate strong correlations between the number of lines in generated Gcode and key performance metrics (tensile strength, defect rate, and dimensional accuracy). Notably, some scripts with fewer lines reduced material defects yet slightly degraded dimensional accuracy, while more complex scripts improved measurement fidelity but also introduced minor flaws. These findings illuminate the trade-offs in AI-driven 3D printing and highlight the method's capacity for ongoing improvement. By exploring future expansions, such as continuous-function printing trajectories and multi-material prints, this study shows that AI-based Gcode generation can significantly advance 3D printing quality and customization across diverse applications.

关键词： Solid modeling Accuracy Generative AI Large language models Machine learning Predictive models Three-dimensional printing Minimization Trajectory Optimization

来源：评论

学校读者我要写书评

暂无评论

A three-dimensional compliant bowtie-shaped mechanical amplifier to magnify coaxial displacement in a confined space

A three-dimensional compliant bowtie-shaped mechanical ampli...

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Jintaek Im Eunsil Jang Cheol Song Department of Robotics and Mechatronics Engineering DGIST Daegu South Korea

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

This paper proposes a novel form of a three-dimensional coaxial bowtie-shaped mechanical amplifier. The proposed model incorporates a lever mechanism into the Sarrus linkage structure. It allows the target plate to move along one axis with amplified displacement in a parallel manner. The amplifier was assembled after machining the components using a computer numerical control machine. A flexible hinge was incorporated into the amplifier design for simplified fabrication and reduced friction in the actuation mechanism. Castigliano’s theorem is used to build a mathematical model of the proposed mechanical amplifier, and the performance was validated through finite element analysis and prototype fabrication. We achieved the amplification ratio of ×8.44, resulting in the axial displacement up to 86 µm. The demonstrated amplifier is expected to apply to compact microsurgical robots or biomedical imaging apparatus requiring coaxial displacement amplification in confined spaces.

关键词： Fabrication Couplings Technological innovation Resonant frequency Prototypes Predictive models Mathematical models

来源：评论

学校读者我要写书评

暂无评论

INDUSTRIALIZING RESIDENTIAL CONSTRUCTION USING ARTIFICIAL INTELLIGENT (AI) robotics

INDUSTRIALIZING RESIDENTIAL CONSTRUCTION USING ARTIFICIAL IN...

引用

ASME 2022 International Mechanical engineering Congress and Exposition, IMECE 2022

作者： Abaza, Hussein Clark, Austin Schwartz, Aaron Ducre, Henry J. Guerra-Zubiaga, David A. Kennesaw State University Department of Robotics and Mechatronics Engineering MariettaGA United States

ISBN: (纸本)9780791886649

This research investigates using AI robotics in automating wooden residential construction. Residential building construction still depends on manual labor. Automation is used to construct certain buildings such as wood trusses, cabinets, doors, windows, and mechanical systems. However, there is a great need for automating the assembly of the building construction. This research builds a framework on how robotics can automate the construction of significant building components and assemble them in the field. In this approach, walls, roofs, and floors assemble in the area. Several attempts have been made to use robots for wood framing. However, these automation attempts focused only on the structural parts of the wooden construction. The scope of this research includes using multiple robots with conveying belts to incorporate the assembly of the main building components, including the wooden framing, exterior sheathing and siding, electric wiring and trim, plumbing pipes, thermal insulation, vapor barrier, waterproofing, trim, windows, and doors, and first coat painting. Building assemblies will be transported to the field and fit together. The system will integrate mass customization strategies which includes Product Family Architecture and Personalization Design. This approach will improve quality assurance, reduce labor costs, reduce construction time, and reduce material waste. As a proof of concept, the research simulates the use of a robot to assemble walls components. The results showed that using AI robotics to automate wooden residential construction is possible and practical. The advancement in AI robots overcame the inconsistencies in building materials and achieved the goals of this project. Copyright © 2022 by ASME.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Independent Optimization for Robot Path Planning and Dynamic Obstacle Avoidance 19

Independent Optimization for Robot Path Planning and Dynamic...

引用

19th IEEE International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI, HONET 2022

作者： Hall, Terrance Johnson, Christopher Swales, Brighton Koduru, Charles Tanveer, M. Hassan Kennesaw State University Dept. of Robotics and Mechatronics Engineering Marietta United States

ISBN: (纸本)9781665461979

Autonomous robots can be assigned with various tasks such as moving payload, analyzing terrain, and capturing data in an environment. For an Autonomous Mobile Robot (AMR) to execute such tasks the robot (Hussarion ROSbot) will require efficient algorithms and techniques to reference its current location. The robot is relative to surrounding obstacles in its predetermined path. The conducted research study explains the coordinated method used to successfully allow a robot to identify its position in the environment (Gazebo Simulation) and avoid obstructions with increasing velocity - contingent on nearby surroundings. The results show multiple robots individually tasked with distinct roles, while incorporating an obstacle avoidance function used to avoid both static and dynamic obstacles. Such results can be used in the applications of a high-capacity warehouse environments. © 2022 IEEE.

关键词： Multipurpose robots

来源：评论

学校读者我要写书评

暂无评论

Seat-Focused Multi-DOF Exoskeleton Wheelchair Synergy for Continuous Lower-Limb Rehabilitation

Seat-Focused Multi-DOF Exoskeleton Wheelchair Synergy for Co...

引用

IEEE Southeastcon

作者： Razvan Cristian Voicu Charles F Freeman Christopher E Garretson Zoe M Sun Ryan H. Bonus Zachary A Slutzky Niranjan Mukesh Muhammad Hassan Tanveer Yannique Tello Yusun Chang Department of Robotics & Mechatronics Engineering Kennesaw State University Marietta Georgia

ISBN: (数字)9798331504847

ISBN: (纸本)9798331504854

Wheelchair users with limited or nonexistent lower-limb mobility often struggle with significant muscle atrophy, circulatory complications, and other health issues. Although exoskeletons for gait training have shown promise, many are optimized for upright ambulation and overlook individuals remaining fully seated due to clinical or practical constraints. This article presents a seat-focused exoskeleton synergy integrated with a wheelchair to facilitate multi-DOF lower-limb mobilization without requiring transfers or standing maneuvers. The system addresses a critical gap by providing repeated, lower-intensity knee and ankle exercises throughout the day-either passively, actively with assistance, or in a resistive training mode-thus promoting muscle engagement and circulation from a seated position. The exoskeleton leverages the wheelchair's power source and employs modular, adjustable rails to accommodate diverse leg lengths. Emphasis is placed on biomechanical alignment, safe torque control, and user comfort, supported by a model-based controller accounting for inertia, Coriolis effects, and gravity in real time. Bench tests and preliminary trials confirm stable torque output, accurate tracking of desired motion profiles, and minimal burden when attaching or detaching the device. The article introduces modeling for a two-DOF prototype (knee flexion/extension and ankle dorsiflexion/plantarflexion), expandable to include additional joints or degrees of freedom, enabling broader rehabilitation targets such as hip abduction/adduction. By embedding rehabilitative capabilities directly into the wheelchair environment, the proposed approach seeks to close the gap between infrequent clinic appointments and continuous therapy aimed at mitigating muscle ailments. A seat-focused exoskeleton designed for every-day use can facilitate accessible, on-demand rehabilitation and substantially improve long-term health outcomes for mobility impaired users.

关键词： Training Knee Atrophy Ankle Torque Target tracking Wheelchairs Exoskeletons Torque control Muscles

来源：评论

学校读者我要写书评

暂无评论

Experimental and numerical study of deposition mechanisms for cold spray additive manufacturing process

引用

Chinese Journal of Aeronautics 2022年第2期35卷 276-290页

作者： Tianyu YU Mingjun CHEN Zhuoru WU State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150001China School of Mechatronics Engineering Harbin Institute of TechnologyHarbin 150001China Department of Mechanical Engineering Iowa State UniversityAmes 50011USA

Cold spray is an attractive and rapidly developing process for additive manufacturing with high efficiency and precision,repairing and coating,especially in aircraft and aerospace *** spray additive manufacturing deposits micro-particles with large plastic deformation below their melting point,eliminating heat effect zone which could deteriorate the quality of repairing *** particle deposition in cold spray is a complex process which involves high strain rate,high contact pressure and high *** we develop,utilize and validate a thermomechanical model to provide a definitive way to predict deposition mechanics and surface deformation evolution for particle deposition process in cold spray additive *** a single particle and dual particles models were developed to investigate the contact interaction between particle/substrate and particle/*** combinations of particle/substrate materials(Cu/Cu,Al/Al,steel/steel,and nickel/nickel)and process parameters were considered in this *** experimental study was conducted to validate simulation results,providing useful information for understanding the limitations and challenges associated with cold spray additive *** framework provides insights into improving the quality and precision of stress/strain formation,particle interactions and particle deposition in cold spray additive manufacturing process.

关键词： Additive manufacturing Cold spray Finite element analysis Residual stresses Surface morphology

来源：评论

学校读者我要写书评

暂无评论

Development of an Accelerometer-based Data Acquisition System for Hand Gesture Recognition

Development of an Accelerometer-based Data Acquisition Syste...

引用

robotics, Automation, Artificial-intelligence and Internet-of-Things (RAAICON), 2019 IEEE International Conference on

作者： Atique Tajwar Md. Ettashamul Haque Md Mehedi Hasan Department of Robotics and Mechatronics Engineering University of Dhaka Dhaka Bangladesh

ISBN: (数字)9798331534400

ISBN: (纸本)9798331534417

This study presents a novel approach to Human-Robot Interaction (HRI) by employing gesture recognition to control robotic systems, such as bionic arms or manipulators, through accelerometer-based data collection. Using a low-cost glove equipped with an ESP32 microcontroller and accelerometer, data was gathered from 22 participants performing five distinct gestures: a clockwise circle, square, triangle, double tap, and the letter S. After filtering, these gestures were translated into features that trained a small neural network model designed for low-storage microcontrollers like the ESP32. With a performance accuracy of 90.4%, the neural network outperformed existing ensemble learning models, demonstrating its suitability for real-time gesture recognition tasks in embedded robotic systems. This highly efficient model enables seamless and intuitive control of robotic devices by facilitating responsive and natural HRI through gesture recognition. Designed specifically for compact and resource-limited environments, the model addresses the challenges associated with limited computational resources and restricted hardware capabilities. It provides a robust and scalable solution that can be easily integrated into various robotics applications, where gesture-based control is advantageous.

关键词： Microcontrollers Computational modeling Neural networks Human-robot interaction Low-pass filters Gesture recognition Data collection Manipulators Feature extraction Data models

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：