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检索条件"任意字段=2023 3rd International Conference on Detection Technology and Intelligence System, DTIS 2023"

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Using Brightness Distribution in Fundus Images to Automated Glaucoma detection 3

Using Brightness Distribution in Fundus Images to Automated ...

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3rd IEEE international Maghreb Meeting of the conference on Sciences and Techniques of Automatic Control and Computer Engineering, MI-STA 2023

作者： Ahmed, Zakia Lawgali, Ahmed University of Omar Al-Mukhtar Faculty of Sciences Department of Computer Science Albayda Libya University of Benghazi Faculty of Information Technology Department of Computer Science Benghazi Libya

ISBN: (纸本)9798350319897

Glaucoma is a condition of the optic system that can cause vision loss as a result of increased intraocular pressure. The disease is becoming more prevalent, and its diagnosis can be both costly and time-consuming. One prominent area of the retina affected by glaucoma is the optic nerve head, which undergoes structural changes. The goal of the study was to detect glaucoma by analyzing the brightness distribution in optic nerve head fundus images, with statistical parameters serving as the primary means of measurement. Specifically, the mean and standard deviation were extracted as features from the fundus images, representing the central tendency and variation of data within the images. The proposed approach demonstrated highly accurate results, outperforming existing literature in the field. © 2023 IEEE.

关键词： Diagnosis

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3rd international conference on Autonomous Unmanned systems, ICAUS 2023

3rd International Conference on Autonomous Unmanned Systems,...

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3rd international conference on Autonomous Unmanned systems, ICAUS 2023

ISBN: (纸本)9789819711024

The proceedings contain 93 papers. The special focus in this conference is on Autonomous Unmanned systems. The topics include: Multi-UAV Collaborative Search Strategy Based on Improved Genetic Algorithm;Joint Beamforming and Power Allocation in a MIMO Radar Network with Per-antenna Power Control;intelligent Trajectory Planning Algorithm for Unmanned Aerial Vehicles Based on Track Deception Against Radar Networks;Maneuvering Multi-target Tracking Based on DLSTM and Dynamic Association Gate;A DNN-Based GLMB Algorithm for Multi-sensor Multi-target Tracking with Dense Group Clutter;efficient Multiple Extended Target Tracking Based on Minimum Spanning Tree;improved Adaptive Sliding Mode Cooperative Guidance Law with Multi-constraints;a Cooperative Guidance Law with Multi-constraints for Intercepting Maneuvering Target;alleviating Local Optima and Enhancing Path Planning: A Deep Reinforcement Learning Approach for Autonomous Exploration;Research on Target Tracking Algorithm Between UAVs in Unknown Environment;a Maneuver detection-Range Parameterized Cubature Kalman Filter for Bearings-Only Maneuvering Target Tracking;improvement of Ensemble Kalman Filter for Hypersonic Target Tracking;anti-bias Target Association Method Based on Laplacian Spectrum and Kuhn-Munkres Algorithm;Fully Automated UAV Cluster Pollution Source detection Algorithm;Status and Application of Artificial intelligence-Based Cooperative Positioning and Navigation technology for UAV Clusters;a Fusion Method with Information Gains for Distributed Multi-sensor Network;space Targets Tracking Algorithm Based on Improved State Equation with Universal Variable Updating;Multi-UAV Target Localization Based on 3D Object detection and Visual Fusion;Real-World Experiments on Acoustic detection of Small UAVs;relative Localization of Vehicle-to-Drone Coordination Based on Lidar;P-LVIO: A Plane-Based Lidar Visual Inertial Odometry in Urban Environments;a New Threat Assessment Method for Airborne Targets Based on Dynami

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A Novel Cloud-Based Framework for Leaf Disease detection and Classification: Enhancing Plant Health Using Android Applications 3

A Novel Cloud-Based Framework for Leaf Disease Detection and...

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3rd international conference on Advancement in Electronics and Communication Engineering, AECE 2023

作者： Kiran, Ajmeera Namdev, Arpit Chandan, Radha Raman Waghmare, Pravin B. Dhabliya, Dharmesh Gupta, Ankur Mlr Institute of Technology Dept. of Cse Hyderabad Telangana Dundigal India University Institute of Technology Rgpv Dept. of It MP Bhopal India School of Management Sciences Dept. of Computer Science UP Varanasi India Acharya Shrimannarayan Polytechnic Msbte Dept. of Civil Engineering Mumbai India Vishwakarma Institute of Information Technology Dept. of It Maharashtra Pune India Vaish College of Engineering Dept. of Cse Haryana Rohtak India

ISBN: (纸本)9798350330724

The difficult challenge of identifying the leaf disease in agriculture is employed to stop the dangerous epidemic. The majority of plant diseases are brought on by fungus, bacteria, and viruses, with the fungi often attached to the plant's reproductive organs. As a result, bacteria have simpler life cycles and are more dangerous than fungi. Similar to bacteria, viruses are microscopic particles that contain genetic information and protein but no additional protein. Therefore, it is crucial to spot illness in plant leaves. Therefore, the goal of this research is to identify leaf disease in a cloudy environment. The use of smartphones for many applications has increased recently. A brand-new operating system called Android is freely accessible in the Android Market. Thus, this study uses an Android application to develop a cloud-based illness categorization system. © 2023 IEEE.

关键词： Agriculture

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3rd international conference on Autonomous Unmanned systems, ICAUS 2023

3rd International Conference on Autonomous Unmanned Systems,...

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3rd international conference on Autonomous Unmanned systems, ICAUS 2023

ISBN: (纸本)9789819710942

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3rd international conference on Autonomous Unmanned systems, ICAUS 2023

3rd International Conference on Autonomous Unmanned Systems,...

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3rd international conference on Autonomous Unmanned systems, ICAUS 2023

ISBN: (纸本)9789819710904

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Transfer Learning and CNN-Based Vehicle Identification Approach for Hit-and-Run Cases 3

Transfer Learning and CNN-Based Vehicle Identification Appro...

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3rd international conference on Advancement in Electronics and Communication Engineering, AECE 2023

作者： Darji, Krisha Ramoliya, Fenil Trivedi, Chinmay Gupta, Rajesh Kakkar, Riya Tanwar, Sudeep Garg, Deepak Institute of Technology Nirma University Department of Computer Science and Engineering Ahmedabad India School of Computer Science and Artificial Intelligence Sr University Telangana Warangal India

ISBN: (纸本)9798350330724

In the swiftly evolving landscape of the modernized transportation, characterized by unprecedented technological advancements, the escalating frequency of Hit-and-Run incidents on the road poses a critical challenge to the people's well being. In response, we present a pioneering vehicle identification approach leveraging Transfer Learning-enhanced Convolutional Neural Networks (TL-enhanced CNN) to address the Hit-and-Run cases which can endanger the people' life. By harnessing the power of continuous traffic monitoring, camera sensors, and location data, the proposed approach adeptly detects and classifies vehicles involved in Hit-and-Run incidents. This model is trained on diverse vehicular images and the TL-enhanced CNN methodology not only identifies vehicle types, but also extracts essential information within the dynamic monitoring environment. The core of proposed approach lies in an Ensembled CNN model, combining the strengths of Visual Geometry Group (VGG-16), Residual Network (ResNet-50) and InceptionV3, enhancing both accuracy and robustness. Rigorous evaluation, encompassing training parameter analysis, loss curves, accuracy curves, and comprehensive performance metrics, establishes the robustness and efficacy of this proposed approach, thus offering a potent solution to the mounting challenge of Hit-and-Run detection and response in modern transportation systems. © 2023 IEEE.

关键词： Convolutional neural networks

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Fire Risk Management Strategy Considering Arc Failure in an Aging Photovoltaic system 3

Fire Risk Management Strategy Considering Arc Failure in an ...

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3rd international conference on Electrical Engineering and Control Science, IC2ECS 2023

作者： Song, Zhenyu Xing, Chen Li, Ming Zhang, Wenyu Cai, Hongfei Niu, Hongyi State Grid Jibei Zhangjiakou Wind and Solar Energy Storage and Transportation New Energy Co. Ltd Hebei Zhangjiakou China School of Electrical Engineering Hebei University of Technology Tianjin China

ISBN: (纸本)9798350382426

Photovoltaic (PV) power generation systems that have been in service for nearly 10 years exhibit a high probability of direct current (DC) distribution faults, significant fire risks, and dangers. These issues severely affect the operational safety of PV power stations, their power generation, and output capabilities. They also present technical challenges for the station's operation and maintenance in terms of precise fault and fire detection. To address this, we begin with an analysis of faults in production site DC distribution cabinets, revealing the mechanisms behind poor contact, insulation degradation, fault arcs, and the evolution of electrical fires. We analyze the theoretical results of fault arc diagnosis and fire detection technology both domestically and internationally in terms of their effectiveness against operational station arc fires. We propose application solutions for pre-diagnosis of fault arcs and fire detection technologies. Our research results indicate that the fault arc diagnosis and fire detection technology application scheme proposed in this paper compensates for the shortcomings of DC relay protection, which cannot protect against series arc faults. It can effectively diagnose fault arcs and detect smoke and high temperatures to prevent the occurrence and escalation of fires. © 2023 IEEE.

关键词： DC distribution cabinet detection technology electric arc fault mechanism photovoltaic fire

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Kidney Disease detection and Identification Using Artificial intelligence 13

Kidney Disease Detection and Identification Using Artificial...

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13th international conference on Cloud Computing, Data Science and Engineering, Confluence 2023

作者： Saraswat, Tanya Pathak, Savita Sachdeva, Sanya Sahu, Krishna Sawhney, Rahul Amity University Amity School of Engineering and Technology Uttar Pradesh India Benevis Atlanta United States

ISBN: (纸本)9781665462631

Kidney Disease is the 3rd most substantial cause as mentioned and has the highest rate of morbidity and mortality rated all over the world. Chronic Kidney Disease is detected at a very later stage therefore making it one of the most harmful diseases. According to the Electronic Medical Records it is very hard for the detection of Chronic Kidney Disease. Severe medical treatment like hemodialysis is required for the procedures conducted for the curing of Renal Disease. Chronic Kidney disease has affected nearly about 10% of the present day population which itself claims how contagious this disease is. Blood Pressure, Heart Ailment, Glucose Level, Sodium, Potassium are all the causes for the identification of CKD. © 2023 IEEE.

关键词： Diseases

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An Intense systematic Review of Mobile Agent Based Harmful Threats and Attack detection systems in IOT Networks 3

An Intense Systematic Review of Mobile Agent Based Harmful T...

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3rd international conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Vigenesh, M. Ravivarman, G. Singh, Prabhdeep Vaseem Akram, Shaik Sharma, Deepti Tiwari, Mohit Karpagam Academy of Higher Education Department of CSE Coimbatore India Karpagam Academy of Higher Education Department of EEE Tamil Nadu Coimbatore India Graphic Era Deemed to Be University Department of Computer Science and Engineering Uttarakhand Dehradun India Uttaranchal University Uttaranchal Institute of Technology India Uttaranchal University Department of Management Dehradun India Bharati Vidyapeeth's College of Engineering Department of Computer Science and Engineering Delhi India

ISBN: (纸本)9798350399264

A breach is detected by an intrusion detection system (IDS) by analysing events that are deemed risky from a security standpoint in systems and networks. Due to a surge in occurrences involving network security, organisations must implement IDS for the protection of sensitive data. Both intrusions coming from outside a network and those coming from within a distributed network are challenging to identify. IDS should be in charge of processing a sizable volume of data without overwhelming networks and monitoring systems. Due to the flaws and restrictions in centralised IDS, mobile agents (MA) were developed. By identifying harmful activity, these agents can carry out specified actions. From earlier works of literature, it was deduced that most of the existing IDS based on MA are not significantly effective © 2023 IEEE.

关键词： Internet of things

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3rd international conference on Autonomous Unmanned systems, ICAUS 2023

3rd International Conference on Autonomous Unmanned Systems,...

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3rd international conference on Autonomous Unmanned systems, ICAUS 2023

ISBN: (纸本)9789819711062

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