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MOPO-HBT: A movie poster dataset for title extraction and recognition

Multimedia Tools and Applications 2024年第18期83卷 54545-54568页

作者： Ghosh, Mridul Roy, Sayan Saha Banik, Bivan Mukherjee, Himadri Obaidullah, Sk Md Roy, Kaushik Dept. of Computer Science Shyampur Siddheswari Mahavidyalaya Howrah India Dept. of Computer Science & Engineering Aliah University Kolkata India Dept. of Electronics & Electrical Communication Engineering IIT Kharagpur Kharagpur India TISA Lab Dept. of Computer Science West Bengal State University Barasat India

Real-world images often encompass embedded texts that adhere to disparate disciplines like business, education, and amusement, to name a few. Such images are graphically rich in terms of font attributes, color distribution, foreground-background similarity, and component organization. This aggravates the difficulty of recognizing texts from these images. Such characteristics are very prominent in the case of movie posters. One of the first pieces of information on movie posters is the title. Automatic recognition of movie titles from images can aid in efficient indexing as well as information conveyance. However, it is accompanied by other texts like the names of actors, producers, taglines, dates, etc. Though the organization of components is somewhat similar across different film industries like Tollywood (West Bengal), Bollywood (Mumbai), and Hollywood (Los Angeles), the graffiti patterns differ in multifarious instances. To address the problem of movie title understanding, we propose a dataset named MOvie POsters-Hollywood Bollywood Tollywood (MOPO-HBT) that encompasses movie posters from the aforementioned industries. The entire dataset is publicly available (http://***/11564) for research purposes. The baseline results of title identification and recognition were obtained with a CNN-based (Convolutional Neural Network) approach, wherein the titles were extracted using the M-EAST (Modified-Efficient and Accurate Scene Text) detector model. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023.

关键词： Character recognition

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Enhancing Bikers' Safety and Coordination: A LoRa-Enabled Wearable system for Smart Cycling 4

Enhancing Bikers' Safety and Coordination: A LoRa-Enabled We...

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4th International Conference on Soft Computing for Security Applications, ICSCSA 2024

作者： Krishna Prasad, D.S. Sandeep Kumar, S. Deeksha, G.D. Rao, Manasa Megha, S. Shashwathi, N. Dept. of Computer & Communication Engineering Nitte Karnataka574110 India

ISBN: (纸本)9798331515720

In recent years, the popularity of biking, especially mountain biking, has surged, drawing enthusiasts seeking adventure and adrenaline amidst rugged landscapes. However, with this surge in popularity comes an increased awareness of the safety challenges inherent in the sport, particularly in remote or challenging terrains where traditional communication methods often fail to provide adequate support. Recognizing these challenges, the paper presents a LoRa-enabled wearable system tailored to enhance safety and coordination for mountain bikers, focusing on challenging terrain scenarios. By incorporating GPS functionality, the system delivers crucial information such as status updates and emergency notifications, thereby markedly elevating safety standards for riders. Furthermore, the project enables real-Time communication in network-deficient areas, effectively surmounting communication hurdles posed by mountainous landscapes. Leveraging LoRa technology extends the communication range, guaranteeing uninterrupted connectivity and empowering bikers to traverse rugged terrains with heightened assurance and security. © 2024 IEEE.

关键词： Global positioning system

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Hardware Implementations of Dehazing Algorithms 18

Hardware Implementations of Dehazing Algorithms

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18th INDIAcom;11th International Conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Akash, E. Ashokkumar, S.R. Banupriya, N. Subash Thangam, K. Sanjay Kumar, N. Jananeshwaran, M. Sri Eshwar College of Engineering Dept. Computer and Communication Engineering Coimbatore India

ISBN: (纸本)9789380544519

Haze, a phenomenon arising from the scattering of light by atmospheric particles, imparts undesirable visual artifacts and degradation to images, posing challenges across various applications. This review paper delves into the realm of dehazing algorithms, with a specific focus on their hardware implementations. The introductory section lays the groundwork by elucidating the nature of haze, its diverse types, and the detrimental impacts it inflicts on image quality through light scattering mechanisms. In response to the pressing need for real-time dehazing solutions, the paper navigates through the landscape of hardware-based dehazing algorithms This review addresses the intricate hurdles encountered in translating dehazing algorithms into hardware architectures. These challenges span architectural design considerations, power efficiency optimizations, memory bandwidth management, and algorithmic adaptation for parallel processing. To benchmark the advancements achieved thus far, the paper delves into a comparative analysis of diverse hardware implementations and their corresponding results. Notable architectural choices, from FPGA (Field-Programmable Gate Array) to specialized ASICs (Application-Specific Integrated Circuits) are dissected in terms of their performance metrics, energy efficiency, and suitability for real-time applications. This assessment also encompasses an examination of trade-offs between accuracy and computational speed in various hardware contexts. Drawing insights from the reviewed literature, this paper offers a comprehensive overview of the strides taken in the field of hardware-based dehazing algorithms. The synthesis of challenges, architectures, and comparative results provides a roadmap for future research directions, offering insights into potential areas of improvement and innovation. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： ASICs FPGA Hardware Implementation Haze Image Dehazing VLSI

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Solar Energy based Smart Home Monitoring and Automation using IOT 4

Solar Energy based Smart Home Monitoring and Automation usin...

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4th International Conference on Power, Energy, Control and Transmission systems, ICPECTS 2024

作者： Dharmaraj, N. Adithyaa, A. Satyanarayanaa, H. Mouleesh, Y. Rupesh, S. Priyadharshini, K. Rajalakshmi Institute of Technology Dept. of Electronics and Communication Engineering Chennai India Rajalakshmi Institute of Technology Dept. of Computer and Communication Engineering Chennai India

ISBN: (数字)9798331508845

ISBN: (纸本)9798331508845

In the pursuit of sustainable living and energy efficiency, integrating renewable energy sources with smart home technologies has become increasingly important. This paper presents a novel system that utilizes solar energy as the primary power source for a smart home, combined with Internet of Things (IoT) technology for monitoring and automation. The primary goal of this project is to reduce waste in conventional ways by making extensive use of energy recovery sources, enhancing safety, and removing environmental impact. Optimizing the equipment's use of program energy in accordance with the actual time of solar power generation is one of the key goals. Another is enhancing the effectiveness of energy transfer through remote monitoring and control using data and smartphone applications. The integration of Internet of Things (IOT) technology with solar energy systems is critical to the sustainability, efficiency, and administration of residential surroundings. This article investigates the deployment capabilities of the Internet of Things (IOT) for solar household energy system automation and monitoring. Future house automation will rely on solar energy and Internet of Things monitoring technologies once this work is completed. © 2024 IEEE.

关键词： Smart homes

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Designing and Implementing an IoT-Based Long-Distance Fire-Extinguishment system 'Stationary 3-Axis Fire-Emergency Response Base' 8

Designing and Implementing an IoT-Based Long-Distance Fire-E...

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8th International Conference on Electronics, Materials engineering and Nano-Technology, IEMENTech 2025

作者： Kundu, Shyantan Dey, Swarajit Abdullha, Md. Mustafa Sen, Gobinda Gangopadhyay, Malay Institute of Engineering & Management Dept. of Computer Science & Engineering Kolkata India Institute of Engineering & Management Dept. of Electronics & Communication Engineering Kolkata India

ISBN: (纸本)9798331520762

This paper presents the design and implementation of an Internet of Thing (IOT)-based long-distance fire-extinguishment system named 'Stationary 3-Axis Fire-Emergency Response Base' (STAFERB). The system aims to provide immediate response to fire hazards in various environments, including residential areas, building complexes, commercial areas, small-scale industries, large factories, dense slum areas, and remotely located forest regions. The proposed STAFERB is designed to receive fire location coordinates, fire intensity, and probable cause information. It then calculates the path of a projectile based on considering obstacles and self-detection of a clear line of sight to reach the t1arget location. The system uses this information to select the appropriate speed and type of fire retardant. The designed STAFERB features robust communication, self-path detection, auto-orientation, and reduced response time, making it a significant advancement in fire-fighting technology. Experimental results demonstrate the effectiveness of the proposed STAFERB in mitigating fire hazards and hence can be well suited for real-time disaster management. © 2025 IEEE.

关键词： Fire hazards

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A Dual-Action Approach to Mosquito Control: Harnessing Mosquitoes Affinity for Light with Metofluthrin's Lethality 18

A Dual-Action Approach to Mosquito Control: Harnessing Mosqu...

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18th INDIAcom;11th International Conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Mittal, Manisha Singh, Mahender Dewan, Prachi Singh, Prabhmeet Dept. of Electronics and Communication Engineering New Delhi India Dept. of Computer Science and Engineering New Delhi India

ISBN: (纸本)9789380544519

Amidst rapid urbanization and fluctuating climatic patterns, the world witnessed a surge in mosquito-borne diseases, escalating global health concerns. Mosquitoes, often dismissed as mere irritants, are carriers for a spectrum of conditions, including malaria, dengue, and the Zika virus, with WHO reporting large numbers of dengue cases annually. This review delves deep into the observation of mosquito behavior and the challenges in eradicating these pests, emphasizing the inefficacy of singular sensory targeting repellents. This paper introduces a pioneering device, combining the mosquito's affinity towards light with the suffocating effects of metofluthrin, offering a holistic solution. By the combination of advanced engineering with a comprehensive understanding of mosquito behavioral dynamics, this device promises not only to repel but to substantially reduce these vectors, fostering safer indoor spaces. Through a detailed exploration of current methodologies and the introduction of this integrated strategy, this paper provides insights into creating a healthier, mosquito-free environment. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： fluorescent light metofluthrin mosquito control mosquito-borne diseases multifaceted sensory system

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Key Vertex Pairs Extraction for Graph Classification Based on Probability Distribution Learning 6

Key Vertex Pairs Extraction for Graph Classification Based o...

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6th International Conference on Artificial Intelligence in Information and communication, ICAIIC 2024

作者： Huang, Jianming Kasai, Hiroyuki WASEDA University Dept. of Computer Science and Communication Engineering Tokyo Japan

ISBN: (纸本)9798350344349

Graph classification is a hot topic of machine learning for graph-structured data, and it is also a very potential and valuable research. However, the difficulty of graph classification is challenging and special, which is quite different from the normal classification problems. One of the most difficult points of graph classification is that the numbers of vertex neighbors in graphs are usually variable, which makes the number of weights uncertain and ambiguous. Recent work such like the graph attention network apply the transformer on the graph neural network. However, the learned attentions cannot strictly reveal the importance of each part of graph, which makes the model less explainable. Moreover, for small datasets, it performs less effectively because of the excessive parameters. In order to overcome these difficulties, we propose a lightweight model with an edge weighting function based on the probability distributions of node pair features learned by the Gaussian mixture model. Although the proposed framework is simple, the experimental results shows its effectiveness on small datasets. © 2024 IEEE.

关键词： Graph neural networks

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Enhancing Spam Email Detection with a Soft Voting Ensemble of Optimized Machine Learning

Enhancing Spam Email Detection with a Soft Voting Ensemble o...

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2024 IEEE International Conference on Computing, Applications and systems, COMPAS 2024

作者： Tazwar, Asif Daiyan, Md Mahir Jiabul Hoque, Md Saifuddin, Mohammed Khaliluzzaman, Md. International Islamic University Chittagong Dept. of Computer and Communication Engineering Chittagong Bangladesh Fse International Islamic University Chittagong Dept. of Computer and Communication Engineering Chittagong Bangladesh Fse International Islamic University Chittagong Dept. of Computer Science and Engineering Chittagong Bangladesh

ISBN: (纸本)9798331529765

Spam email detection is crucial for cybersecurity, as it protects user privacy and reduces security risks. The persistent presence of spammers necessitates continuous improvements in spam filtering measures. To address this challenge, this study employs Grid Search Optimizer to fine-tune the parameters of four distinct classifiers: Support Vector Machine (SVM), Random Forest, Naive Bayes, and XGBoost. Soft Voting serves as the final classifier, enhancing overall accuracy by integrating results from optimized classifiers to detect and classify spam emails across the Spam Mails Dataset and Enron1 Dataset. The experimental study compared the proposed model with relevant works and found that hyperparameter tuning and Soft Voting significantly enhanced its performance compared to existing approaches. The proposed ensemble model outperformed individual classifiers, achieving accuracies of 99.32% and 99.12%, respectively. Also, the ensemble model demonstrated an AUC of 1.00 on both datasets, indicating its effectiveness in distinguishing between spam and ham emails. This approach surpasses prior studies in accuracy, generalization, and robustness by innovatively combining Grid Search and Soft Voting. The constructed model exhibits high effectiveness and efficiency in the detection of spam emails. © 2024 IEEE.

关键词： Decision trees

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Moth flame optimization algorithm for efficient feature selection and hybrid classification technique for intrusion detection system

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Multimedia Tools and Applications 2025年 1-21页

作者： Keerthanarani, U. Selvakumar, V. Singaravelan, S. Raja, S. Edwin Thenmozhi, K. Shunmugam, D. Arun Dept. of Computer Science and Engineering P.S.R Engineering College Sivakasi India Dept.Of Computer Science and Engineering Vel Tech Rangarajan Dr Sagunthala R & d Institute of Science and Technology Chennai Avadi India Dept. Of Computer Science and Engineering Coimbatore Institute of Engineering and Technology Coimbatore India Dept. Of Electronics and Communication Engineering P.S.R Engineering College Sivakasi India

The rapid expansion of the Internet of Things (IoT) brings numerous benefits but further presents fresh difficulties, especially in terms of security. The distributed and interconnected nature of IoT devices makes them susceptible to various security threats. An Intrusion Detection system (IDS) plays a crucial role in safeguarding IoT networks by monitoring, detecting, and responding to potential security incidents. The Internet of Things (IoT) connects billions of devices, sensors, and systems, transforming industries and everyday life. However, this extensive interconnectivity also introduces significant security risks, making Intrusion Detection systems (IDS) a critical component for safeguarding IoT environments. Feature selection is a crucial aspect of building effective Intrusion Detection systems (IDS). Selecting relevant features not only helps in achieving better classification accuracy but also contributes to reducing false alarm rates. In the proposed system a moth flame optimizer is utilized to select the efficient features from the dataset, overall accuracy of over 97%. Further it is classified employing Random Forest and J48 classifier which attains high classification accuracy and low false alarm rate. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Feature Selection

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A 4x4 MIMO Antenna Array for the Wi-Fi7Access Point on a Metal Wall Application

A 4x4 MIMO Antenna Array for the Wi-Fi7Access Point on a Met...

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2024 International Symposium on Antennas and Propagation, ISAP 2024

作者： Su, Hsin-Lung Zhan, You-Sheng Dept. of Computer and Communication National Pingtung University Taiwan Dept. of Computer Science and Information Engineering National Pingtung University Taiwan

ISBN: (纸本)9798350364774

A 4×4 CPW MIMO Antenna array with an artificial magnetic conductor (AMC) reflector is presented for Wi-Fi7 access point on a metal wall application in the study. The 10-dB impedance of the integrated MIMO antenna array covers the Wi-Fi 7 operating bands, and the transmission coefficients are under -15 dB in the whole Wi-Fi7 bands. This proposed integrated MIMO antenna is low profile and has good total radiation efficiency (over 60%). The height of the integrated MIMO antenna array is 6.325 mm. © 2024 IEEE.

关键词： Wireless local area networks (WLAN)

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