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Empirical Seabed Image Classification Using Labeled Machine Learning Techniques

Empirical Seabed Image Classification Using Labeled Machine ...

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Innovations in Communications, Electrical and computer engineering (ICICEC), International conference on

作者： Rajesh Sharma R Akey Sungheetha Rajiv Gandhi K Sasikala Rani GGS Pradeep Ellappan V Department of CSE Alliance University Bangalore India Government Arts and Science College for Women Paramakudi India Department of ECE Mahindra College of Engineering Salem India

ISBN: (数字)9798350376517

ISBN: (纸本)9798350376524

This examine affords an empirical method to seabed photo class through the software of categorized systems getting to know techniques. The studies leverage a dataset of categorized seabed photos to teach and examine diverse systems getting to know algorithms for correct class. Through systematic experimentation and analysis, the effectiveness of various algorithms in discerning seabed capabilities is assessed. The findings contribute to advancing automatic seabed photo analysis, imparting insights into the feasibility and overall performance of systems to know techniques for underwater surroundings characterization.

关键词： Technological innovation Systematics Machine learning algorithms software algorithms Machine learning software Oceanography Classification algorithms Environmental management Image classification

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TSN vs I3D vs Pose-C3D: Action Recognition in Basketball using SpaceJam Dataset 24

TSN vs I3D vs Pose-C3D: Action Recognition in Basketball usi...

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7th International conference on Computational Intelligence and Intelligent systems, CIIS 2024

作者： Chiura, Tafadzwa Blessing Van Der Haar, Dustin Academy of Computer Science and Software Engineering Faculty of Science University of Johannesburg Gauteng Johannesburg South Africa

ISBN: (纸本)9798400717437

Most of the research conducted in action recognition is mainly focused on general human action recognition, and most of the available datasets support studies in general human action recognition. In more specific contexts, such as basketball, datasets that are as comprehensive and publicly available are limited. This study proposes taking three popular and mature methods in the field of action recognition, namely Temporal Segment Networks (TSN), Two-Stream CNN using Inflated 3D-convolutional Neural Networks (I3D) and Pose-C3D, and applying them to the SpaceJam dataset, which is a basketball-specific action dataset. All three experiments used pre-trained ImageNet models and were fine-tuned on the SpaceJam dataset. TSN was the oldest of the methods but obtained the best results of the three experiments, scoring a top-1 and top-5 accuracy of 59% and 96%, respectively. I3D was second best, with a top-1 and top-5 accuracy of 41% and 85%, respectively. Pose-C3D came in third, scoring a top-1 and top-5 accuracy of 15% and 50%, respectively. The results show that the models cannot distinguish significantly between some actions, such as ball in hand, pass and dribble. The study shows that it is feasible for context-specific fine-grain action recognition, but more needs to be done to discriminate against similar actions. © 2024 Copyright held by the owner/author(s).

关键词： Convolutional neural networks

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Cognitive Performance Analysis of the Proposed Testbed for OFDMA Wireless System 1

Cognitive Performance Analysis of the Proposed Testbed for O...

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1st International conference on Cyber Physical systems, Power Electronics and Electric Vehicles, ICPEEV 2023

作者： Chennamsetty, Sneha Boddu, Subbarao Mahindra University Department of Electrical and Computer Engineering Hyderabad India

ISBN: (纸本)9798350323566

To evaluate and optimize the performance of wireless systems in a real-time environment, the proposal and development of a testbed play a crucial role. In this paper, we proposed a testbed for analyzing the cognitive performance of the Orthogonal Frequency Division Multiple Access (OFDMA) wireless systems i.e., 4G and 5G. The proposed testbed consists of software-defined radios (SDRs) that enable the dynamic configuration of radio parameters and the emulation of realistic wireless environments. Firstly, the results of the proposed testbed include the real-time active and vacant frequencies of the 4G and 5G cellular networks of the location and the visualization of the frame structure in real-time. Next, transmit and receive the modulated binary data using the proposed testbed and visualize the real-time results at the receiver end. Based on the obtained results, we conclude that the wireless system design research community may use our testbeds as learning platform tools for simulating the 4G and 5G cellular networks in real time. Further, this may be also used for testing the algorithms, protocols, and solutions. © 2023 IEEE.

关键词： Cognitive systems

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IoT based Leakage Detection and Emergency Shutdown 6

IoT based Leakage Detection and Emergency Shutdown

引用

6th International conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Abarna, P.S. Priya, S. Padma Pavalarajan, S. Sivatharani, S. Manshi, M. Department of Computer Science and Business Systems PSNA College of Engineering and Technology Dindigul India

ISBN: (纸本)9798331522667

The risk of gas leaks has grown significantly as a life threatening issue in industrial activities, cooking, and heating. This system integrates automatic reaction mechanisms, real-time monitoring capabilities, and advanced detection technologies in a multifaceted manner to address various dangers. The comprehensive gas leak detection and automatic cut off system is intended to improve safety in a variety of situations, including industrial and residential ones. To precisely identify the existence of dangerous gases like methane and propane, the proposed system combines infrared, electrochemical, and semiconductor types of gas sensors integrated with a mobile application, users may remotely administer and monitor the system in real-time. The system initiates a multi-tiered response upon detecting a gas leak;it sounds an alarm, notifies user-specified The mobile devices about the leak, and turns on an exhaust fan to release concentrated gas. A solenoid valve is used by the system to quickly shut off the gas supply and electricity from any location. The need of user-friendly controls and prompt notifications in emergency situations is highlighted in this paper's discussion of software architecture, sensor integration, and user interface design. Experimental results show that the system is reliable and capable of responding quickly under different circumstances. In future the application of machine learning algorithms for predictive maintenance and the possibility of integrating IoT to further strengthen security protocols. The results emphasize importance to deploy these kinds of extensive safety systems widely in order to reduce the risks associated with gas exposure. © 2025 IEEE.

关键词： Solenoid valves

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Hardware Implementation of Image Processing Morphological and Convolution Operations as SoC on FPGAs 24

Hardware Implementation of Image Processing Morphological an...

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7th International conference on Digital Medicine and Image Processing, DMIP 2024

作者： Moussa, Alfred M. Groves, Richard Rafla, Nader Electrical and Computer Engineering Department Boise State University BoiseID United States

ISBN: (纸本)9798400709586

Efficient image processing architectures are consistently in demand across a multitude of applications, particularly those customized for resource-constrained systems-on-chip (SoC). The increasing need for high-performance image processing in various sectors has driven the development of specialized architectures. However, deploying such architectures on platforms with limited resources, such as SoCs, poses significant challenges. Furthermore, the implementation of complex algorithms to handle large datasets using software solutions often leads to slower response times, prompting exploration into hardware implementations. Field-Programmable Gate Arrays (FPGAs) are becoming popular for hardware implementations because of their attributes: low latency, connectivity, parallel computing capabilities, and flexibility. Consequently, the utilization of FPGA-based implementations has resulted in faster and more efficient performance of unique architectures tailored to specific requirements. This paper presents a novel hardware/software co-design approach to implement erosion, dilation, and neighborhood image processing operations on the FPGA development board, "Zedboard". In this approach, the FPGA is programmed by connecting it to a PC via USB, facilitating the transfer of an image pixel by pixel. The pixels are temporarily stored in on-chip DDR and accessed through DMA (Direct Memory Access) until they are requested by an interrupt signal from the Image Processing IP, at which point they are moved to line buffers for faster processing. Once processed, the image is transmitted back to the PC via UART, facilitating pixel-by-pixel transfer for verification, where it is compared with a reference image generated using Python. This comparison confirms a 99.22% match between the processed image and the reference image, with the discrepancy occurring at the image's edges due to initial padding. Additionally, the time required to process the entire image was measured and displayed

关键词： System-on-chip

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Exploring Faster R-CNN Algorithms for Object Detection

Exploring Faster R-CNN Algorithms for Object Detection

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software, systems and Information Technology (SSITCON), International conference on

作者： Abhishek Thoke Sakshi Rai Department of Computer Science and Engineering LNCT University Indore India Department of Computer Science and Engineering LNCT University Bhopal Bhopal India

ISBN: (数字)9798350352931

ISBN: (纸本)9798350352948

The task of object detection is widely recognised as a prominent challenge in computer vision applications, particularly in the domains of robotics, autonomous vehicles, and augmented reality. Hence, this paper examines Faster RCNN, a well embraced object identification model that effectively combines speed and accuracy. The authors evaluate several novel models, such as Sparse R-CNN, Cascade R-CNN, Loss-Guided Attention RCNN, Global Context Aggregation RCNN, and others, to demonstrate their unique features and benefits in addressing the challenges of dense object candidates and limited training data. This paper presents a performance evaluation of these models on the COCO dataset, elucidating their accuracy and usefulness for different object detecting applications. The authors conclude that the Sparse R-CNN model outperforms other models in terms of average precision. They also offer recommendations for future optimisation of object identification models in terms of architecture to better suit the demands of real-time processing.

关键词： Performance evaluation Accuracy Computational modeling Training data Object detection computer architecture software systems Real-time systems Object recognition Optimization

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Research on the Process Efficiency of Metro Security CheckSystem Under the Perspective of Spatial Guidance 15th

Research on the Process Efficiency of Metro Security CheckSy...

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15th International conference on Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management (DHM)

作者： Yuan, Yihong Zhang, Haoze OuYang, Ruolei Tan, Jinbang Shen, Yaodong South China Univ Technol Guangzhou Peoples R China

ISBN: (纸本)9783031610653;9783031610660

Metro is one of the most important forms of public transportation in Chinese cities. With the continuous expansion and development of metro networks in China's major cities, ensuring the safety of passengers has become a key part of metro operation and management. However, there are some efficiency and human factors engineering deficiencies in the current metro security system. Some researchers have studied the efficiency of subway security systems and their influencing factors in subway or railroad stations. However, in actual subway stations, the spatial guidance in front of and behind the screening area is also one of the causes of congestion in the screening area. This study focuses on the deficiencies of spatial guidance in the subway, and the resulting congestion in the subway station, which leads to a reduction in the efficiency of the screening system. The implementation plan of this study is to explore the spatial guidance system of Guangzhou Metro, summarize the influencing factors of congestion, quantify and extract data for the influencing factors, and establish a model and data analysis. The interview method was used to invite volunteers to participate, and the information from the interviews was used for data statistics to quantify the influencing factors caused by the spatial guidance system, to establish an appropriate model for the influencing factors, and to determine the significant influencing factors of the spatial guidance on the congestion of people with respect to the data fed back from the model. The collected data and information are coded using the rooted theory research method, analyzed with the help of auxiliary software, and finally, three categories of first-level core influence factors of site layout design, guide signs, and human factors and corresponding second- and third-level subcategories are refined, and a system of influence factors on the efficiency of the process of the security system under the perspective of spatial guidanc

关键词： Subway security screening Spatial guidance Human factors engineering Rootedness theory

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Attention-aware CNN model for Traffic Signs Classification

Attention-aware CNN model for Traffic Signs Classification

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2022 International conference on Cloud Computing, Big Data Applications and software engineering, CBASE 2022

作者： Gu, Xiangsheng Lang, Qiuyi Lin, Fu Wang, Pengfei University of California Donald Bren School of Information & Computer Science Irvine United States Queen's University Belfast Computer Science Belfast United Kingdom York University Canada Leicester International Institute Dalian University of Technology Lassonde School of Engineering Panjin China Dalian University of Technology Leicester International Institute Panjin China

ISBN: (纸本)9798350396393

Autonomous vehicle driving systems have become one of the most important topics recently, some people assert that they can identify traffic signs automatically, which is a revolutionary improvement for transportation;however, the accuracy of autonomous vehicle driving systems still remains controversial. Therefore, this research analyzes the German Traffic Sign Benchmark dataset, in three different ways: AlexNet, VGG-16, and ResNet-50 of autonomous vehicle driving systems, to compare the best approach for identifying traffic signs. One can conclude that AlexNet, VGG-16 and ResNet-50 performed well, as they got an accuracy score of 95%, 95%, 89% respectively. To improve the classification accuracy to achieve nearly 100% for total security, Bottleneck Attention Module (BAM) is examined as a way of improving the classification accuracy of models and it is confirmed that BAM is able to boost the accuracy score of select models. © 2022 IEEE.

关键词： Traffic signs

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Validating the Correctness of Reactive systems Specifications Through Systematic Exploration 22

Validating the Correctness of Reactive Systems Specification...

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ACM/IEEE 25th International conference on Model Driven engineering Languages and systems (MODELS)

作者： Ma'ayan, Dor Maoz, Shahar Rozi, Roey Tel Aviv Univ Tel Aviv Israel

ISBN: (纸本)9781450394666

Reactive synthesis is an automated procedure to obtain a correct-by-construction reactive system from its temporal logic specification. While the synthesized system is guaranteed to be correct w.r.t. the specification, the specification itself may be incorrect w.r.t. the engineers' intention or w.r.t. the requirements or the environment in which the system should execute in. It thus requires validation. Combinatorial coverage (CC) is a well-known coverage criterion. Its rationale and key for effectiveness is the empirical observation that in many cases, the presence of a defect depends on the interaction between a small number of features of the system at hand. In this work we propose a validation approach for a reactive system specification, based on a systematic combinatorial exploration of the behaviors of a controller that was synthesized from it. Specifically, we present an algorithm to generate and execute a small scenario suite that covers all tuples of given variable value combinations over the reachable states of the controller. We have implemented our work in the Spectra synthesis environment. We evaluated it over benchmarks from the literature using a mutation approach, specifically tailored for evaluating scenario suites of temporal specifications for reactive synthesis. The evaluation shows that for pairwise coverage, our CC algorithms are feasible and provide a 1.7 factor of improvement in mutation score compared to random scenario generation. We further report on a user study with students who have participated in a workshop class at our university and have used our tool to validate their specifications. The user study results demonstrate the potential effectiveness of our work in helping engineers detect real bugs in the specifications they write.

关键词： Specifications

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Blind Hurdle Stick: Android Integrated Voice-based Intimation Via GPS with Panic Alert System

Blind Hurdle Stick: Android Integrated Voice-based Intimatio...

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2023 International conference on Innovative Computing, Intelligent Communication and Smart Electrical systems, ICSES 2023

作者： Rajalakshmi, D. Rani, P. Shobha Lakshmi Bhavana, Talapaneni Emani, Viveka Swetha, Reddy R.M.D Engineering College Department of Computer Science and Engineering Tiruvallur Kavaraipettai601 206 India

ISBN: (纸本)9798350319200

There are currently many blind assistive systems in use around the world, but none that are designed specifically to guide the visually impaired and keep tabs on their every move in case of an emergency or to locate them as part of a group that has become disoriented. In this study, we introduce a voice-based, GPS/GSM cooperative blind stick with an integrated emergency alarm system for navigating obstacles. A pair of glasses that are connected to an Android app can guide the visually impaired through the system. The programme generates voice instructions in either Hindi, Kannada, or English based on the location of obstacles, allowing the blind person to move freely throughout their surroundings. In addition, a panic button or voice commands make it possible for a blind person to send an SMS to a predetermined number without ever having to physically touch the phone. The blind-assistive app uses GPS and GSM to determine location, then transmits that information to a server. By using yet another android software that indicates the user's present location on Google Map, a blind person's every step may be tracked and watched. The system's primary goal is to give the visually impaired with an efficient and straightforward navigational tool that contributes to artificial vision by illuminating the dynamic and static items in their immediate surroundings. © 2023 IEEE.

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