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Forest Fire and Landmines Identification with the Support of Drones Surveillance for Better Environmental Protection: A Survey 4

Forest Fire and Landmines Identification with the Support of...

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4th International conference on Smart Systems and Inventive Technology, ICSSIT 2022

作者： Sivabalaselvamani, D. Selvakarthi, D. Rahunathan, L. Munish, M. SaravanaKumar, R. Sruthi, S. Department of Computer Applications Kongu Engineering College Tamilnadu Perundurai638060 India Department of EIE Kongu Engineering College Tamilnadu Perundurai638060 India

ISBN: (纸本)9781665401180

A robotics mechanism is a successful technology for different types of products with the expected output. the drone-based Unmanned Aerial Vehicle (UAV) was developed and used for different applications from this robot mechanism. Here, Unmanned Aerial Vehicle (UAV) was developed with Magnetometer Sensor, Temperature sensor, and Night vision camera. Magnetometers are commonly used in geophysical surveys to measure the Earth's magnetic field, identify magnetic anomalies, and estimate the dipole moment of magnetic materials. the landmines can be detected using the help of magnetometer sensor. A temperature detector is a device that measures the temperature of its context and converts the input line into electronic data to record researcher or signal temperature changes. Night vision camera is that the Image or tape- hung finding that uses both graphical and electrical camera detectors to allow mobile objects within the monitored environment. Based on this module, the Unmanned Aerial Vehicle (UAV) will fly in the morning, night, and smoky regions, unknown activities, and identify the forest fire with an emergency purpose. Using Temperature sensor it will detect the temperature and identify the forest fire and give response notification to the controller. © 2022 IEEE

关键词： Drones

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4th International conference on Applied Technologies, ICAT 2022

4th International Conference on Applied Technologies, ICAT 2...

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4th International conference on Applied Technologies, ICAT 2022

ISBN: (纸本)9783031249846

the proceedings contain 113 papers. the special focus in this conference is on Applied Technologies. the topics include: Automatic Evaluation of Physiotherapy Activities Using Deep Learning Techniques;multivariable Control Approach Applied to the Embryo Incubation Process of Gallus Gallus Domesticus;discovering Visual Deficiencies in Pilots Candidates Using Data Mining;an Electronic Equipment for Measuring Color Difference Between Tissues Based on Digital Image Processing and Neural Networks;artificial Intelligence-Based Banana Ripeness Detection;U-Net vs. TransUNet: Performance Comparison in Medical Image Segmentation;access Control through Mask Detection and Estimation of People Capacity in Covered Premises;customer Segmentation in Food Retail Sector: An Approach from Customer Behavior and Product Association Rules;Bibliometric Analysis of Web of Science Database STEM Fields in Engineering and Mathematics. Ecuador’s Case Study;smart Antenna Array for Optimal Electromagnetic Energy Capture;image Processing Method to Estimate Water Quality Parameter;use of the Student Engagement as a Strategy to Optimize Online Education, Applying a Supervised Machine Learning Model Using Facial Recognition;crime Data Analysis Using Machine Learning Models;Gene therapy as a Solution to Genetic Diseases through DNA Manipulation;Vulnerability of CAPTCHA Systems Using Bots with computer vision Abilities;military Leadership in the Ecuadorian Army;analysis of Key Variables for Ecuadorian Defense Industry Development;the Prioritization of External Security as a Means of Guaranteeing Multidimensional Security and Economic Growth;Comparative Study of Deep Learning Algorithms in the Detection of Phishing Attacks Based on HTML and Text Obtained from Web Pages;ground robot for Search and Rescue Management;virtual Training Module for the Production of Rubber Adhesives through the Production of Cyclopentenol.

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4th International conference on Applied Technologies, ICAT 2022

4th International Conference on Applied Technologies, ICAT 2...

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4th International conference on Applied Technologies, ICAT 2022

ISBN: (纸本)9783031249709

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4th International conference on Applied Technologies, ICAT 2022

4th International Conference on Applied Technologies, ICAT 2...

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4th International conference on Applied Technologies, ICAT 2022

ISBN: (纸本)9783031249778

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Environmental Sound Detection based on Acoustic Multidimensional Synergistic Features and MobileNet-EAL 4

Environmental Sound Detection based on Acoustic Multidimensi...

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4th International conference on robotics and computer vision, ICRCV 2022

作者： Yu, Baocheng Liao, Chuyuan Xu, Wenxia Wei, Ming Lv, Canjiong Li, Jiaxin Wuhan Institute of Technology School of Computer Science and Engineering Wuhan China Wuhan FiberHome Technology Service Co. Ltd. Wuhan China

ISBN: (数字)9781665481700

ISBN: (纸本)9781665481700

For the problem of environmental sound detection in complex environments, the environmental sound detection method based on acoustic multidimensional synergistic features and MobileNet-EAL is proposed. Firstly, the acoustic multidimensional synergistic features of the input audios are extracted to achieve the complementary frequency and time domain information, the complementary static and dynamic information to enhance the ability to express the temporal characteristics of the sound signal. Secondly, the ECA-Net channel attention mechanism is added to the MobileNet-EAL network model proposed to make the model ignore the influence and interference caused by the background sound. Meanwhile, the Leaky ReLU activation function is also used to enhance the model's extraction of negative audio feature information to achieve sound detection in complex environments. the experimental results show that the classification accuracy reaches 91.4% on the UrbanSound8K dataset. Compared with traditional environmental sound recognition methods, the method adopted in this paper has obvious advantages in recognition rate and recognition efficiency. © 2022 IEEE.

关键词： Feature extraction

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Face Expression Recognition Based on Lightweight Fused Attention Mechanism 4

Face Expression Recognition Based on Lightweight Fused Atten...

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4th International conference on robotics and computer vision, ICRCV 2022

作者： Yu, Baocheng Zhang, Guanyu Xu, Wenxia Wei, Ming Wuhan Institute of Technology School of Computer Science and Enginerring Wuhan China Wuhan FiberHome Technology Service Co. Ltd. Wuhan China

ISBN: (数字)9781665481700

ISBN: (纸本)9781665481700

To address the problems of redundant model counts, large computational effort, poor targeting of effective feature extraction and easy loss of large amount of information in traditional convolutional neural networks for expression recognition, a lightweight fused attention mechanism approach for face expression recognition is proposed. the method is based on ResNet convolutional neural network, and the depthwise separable convolutional module is added in the feature extraction stage to reduce the number of parameters, and then the attention mechanism of the fusion channel is used to improve the extraction and representation ability of the model for important feature information. the PReLU is used to replace the ReLU to prevent Dying ReLU problems. the model has been simulated on the public RAF-DB dataset. the results show that the accuracy of facial expression recognition reached 85.53%, while the number of parameters and computational effort are kept at low levels. the results verify the effectiveness and superiority of the improved model. © 2022 IEEE.

关键词： Convolution

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Deep Learning Based Binocular Detection and Localization Method for Roses 4

Deep Learning Based Binocular Detection and Localization Met...

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4th International conference on robotics and computer vision, ICRCV 2022

作者： Yin, Shuyuan Xu, Wenxia Yu, Baocheng Li, Jiaxin Liao, Chuyuan Lv, Canjiong Wuhan Institute of Technology School of Computer Science and Engineering Wuhan China

ISBN: (数字)9781665481700

ISBN: (纸本)9781665481700

Aiming at the problems that interfere with the distance detection of flowers, such as light changes and occlusion of branches and leaves in rose plantations, this paper proposes a deep learning-based binocular vision detection and localization method for roses in complex scenes. Firstly, the attention mechanism Convolutional Block Attention Module (CBAM) is added to the neck layer of YOLOv5 (You Only Look Once) to improve the convergence speed and detection accuracy of the model. Secondly, the Efficient Intersection over Union (EIOU) loss function is used to calculate the length and width of the target frame separately, which solves the problem of large errors in the horizontal and vertical directions. Finally, the Oriented Fast and Rotated Brief (ORB) algorithm is used for matching the feature points and the Hamming distance is added to discriminate the similarity between the descriptors, and then the target detection results are used to constrain the feature points. At the same time, the optimal feature point pair in the flower area is extracted to obtain effective parallax and realize real-time target ranging. the experimental results show that compared with the previous algorithm, the improved algorithm has a 3% increase in accuracy and a 10fps increase in speed. Within a certain range, the average relative error between the measured distance and the actual distance is less than 2%, which meets the flower detection and distance detection requirements of picking robots in rose plantations. © 2022 IEEE.

关键词： Binocular vision

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Multiple Dynamic Object Tracking for Visual SLAM 4

Multiple Dynamic Object Tracking for Visual SLAM

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4th International conference on robotics and computer vision, ICRCV 2022

作者： Hubei, Fuxin Liu Zhang, Yanduo Li, Xun Wuhan Institute of Technology Hubei Key Laboratory of Intelligent Robot School of Computer Science and Engineering China

ISBN: (数字)9781665481700

ISBN: (纸本)9781665481700

the assumption based on scene rigidity has been accepted widely in visual SLAM framework. However, the supposition limits the development of SLAM algorithm in the real world. Especially for automatic driving, many complicate cases involved in it, which demands our SLAM system that provides accurate position robustly and perceives the surrounding environment reliably. therefore, in this paper, we propose a novel visual SLAM front-end module, which uses instance segmentation and dense optical flow estimation to ensure the efficient separation of static background and dynamic targets. For potential moving objects, we take advantage of Unscented Kalman Filter (UKF) to track moving targets and update the according moving state. In light of scale inconsistency in the camera pose estimation, we recover the scene structure and obtain the scale factor in the key frame by the depth estimation network. At the end, we integrate the estimated camera pose and dynamic object tracking into a unified visual odometry. In the process of trajectory optimization, we adopt the sliding window mechanism to acquire the spatio-temporal information of the dynamic object. the experiment results show that the tracking of dynamic objects not only can provide rich clues for surroundings understanding, but also help the tracking of camera pose, and then improve the robustness of the SLAM system in dynamic environment. © 2022 IEEE.

关键词： Cameras

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Design of VISUAL SLAM indoor disinfection robot based on STM32 control 4

Design of VISUAL SLAM indoor disinfection robot based on STM...

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4th International conference on robotics, Intelligent Control and Artificial Intelligence, RICAI 2022

作者： Wu, Changzhong Wang, Shengqiang Fan, Wenchao Tai, Wentao University of Jinan Shandong China

ISBN: (纸本)9781450398343

In recent years, the novel corona virus pandemic is raging around the world, and the safety of home environment and public environment has become the focus of people's attention [2]. therefore, the research on disinfection robot has become one of the important directions in the field of machinery and artificial intelligence. this paper proposes a robot with the STM32 MCU as the core of disinfection, and is equipped with a variety of sensors and a camera vision, has the original cloud service management platform, the remote deployment of navigation, based on visual SLAM to realize high precision navigation and positioning, can realize to indoor environment autonomously route planning, automatic obstacle avoidance checking, disinfection, epidemic prevention function, at the same time can pass Bit computer software realizes remote control of robot, which has great development potential. © 2022 ACM.

关键词： Disinfection

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Wavelet Transform LMS Algorithm Based Signal Noising Cancellation Research for Hydraulic System 4

Wavelet Transform LMS Algorithm Based Signal Noising Cancell...

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4th International conference on robotics and computer vision, ICRCV 2022

作者： Yang, Bang Xing Xia Xu, Wen Yu, Bao Cheng Wu, Jing Liu, Peng Huang, Lei Wuhan Institute of Technology Computer Science and Engineering Wuhan China

ISBN: (数字)9781665481700

ISBN: (纸本)9781665481700

the main role of the aircraft hydraulic system is to provide power for the load of the aircraft. the hydraulic pump is the heart of the entire hydraulic system. In this paper, an aircraft hydraulic pump measurement and control test bench was designed. the test bench has a small footprint and can be moved at any time. the test bench can detect the pressure, temperature, flow, pressure pulsation and other signals of the hydraulic pump in real time. It is of great significance for improving the stability of the entire hydraulic system. the signals collected at the test site contain noise, and most of these noises are unstable and have unpredictable statistical characteristics. the LMS algorithm based on the wavelet transform proposed in this paper is applied to the noise reduction of the pressure pulsation signal of the hydraulic system collected. Experimental results show that the noise reduction effect of this algorithm is better than that of the traditional adaptive filtering algorithm. © 2022 IEEE.

关键词： Wavelet transforms

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