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8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Sowmiya, R. Revathi, P. Ragunath, D. Sindhuja, S. Gokila, P. Kalaivani, T. Sns College of Engineering Department of Artificial Intelligence and Data Science Tamilnadu Coimbatore India Bannari Amman Institute of Technology Department of Computer Science and Engineering Tamilnadu Sathyamangalam India Tamilnadu Coimbatore India Info Institute of Engineering Department of Computer Science and Engineering Tamilnadu Coimbatore India

ISBN: (数字)9798350376425

ISBN: (纸本)9798350376425

This study presents a framework for multimodal models to control and interact with computers: The Multimodal-driven computer Interface. A decision-making module is used by the framework to determine what actions are acceptable after it processes user input through a variety of modalities, such as speech, text, and gestures, and runs it through a multimodal fusion algorithm. Platform-specific APIs are then used to carry out these operations on the computer. It runs on Linux, Mac, and Windows platforms and is currently integrated with the multimodal LLM. Although the framework shows promising results, there are still issues with adjusting to different user demands and preferences and increasing the accuracy of mouse click position prediction. Potentially revolutionizing human-computer interaction, the Multimodal-driven computer Interface offers new avenues for accessibility, productivity, and pleasure. © 2024 IEEE.

关键词： Windows operating system

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Lung Cancer Detection Using CNN Based Model 2

Lung Cancer Detection Using CNN Based Model

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2nd International Conference on Disruptive Technologies, ICDT 2024

作者： Chaudhary, Prince Nitin Kumar, Prince Rana, Naman Garg, Payal Gl Bajaj Institute of Technology and Management Department of Computer Science & Engineering Greater Noida India

ISBN: (纸本)9798350371055

Lung cancer can be fatal, but early diagnosis and treatment can save lives. Doctors use x-ray imaging to detect lung cancer, but it can be hard to distinguish cancerous cells from normal ones. computer-aided diagnosis can help doctors make accurate decisions. This research evaluates different computer-aided methods, analyzes the best one, identifies its flaws and limitations, and suggests a model with enhancements. The methods were ranked and compared based on their detection accuracy, and their flaws and limitations were examined. Some methods have low accuracy, while others have high accuracy, but not higher than 90%. The research aims to achieve an accuracy of 91 % or more © 2024 IEEE.

关键词： CNN Lung Cancer ResNet50 VGG16

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SpeakSmart: Empowering Public Speakers, Elevating Every Speech 8

SpeakSmart: Empowering Public Speakers, Elevating Every Spee...

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8th IEEE International Conference on Computational System and Information technology for Sustainable Solutions, CSITSS 2024

作者： Vaidya, Chandu Haldar, Dipesh Nityan Lohi, Pranjal Yuvraj Rahman, Adeebur Mohsinur Harshita, P. Siriya, Dipesh Khemch S B Jain Institute of Technology Management and Research Computer Science and Engineering Nagpur India

ISBN: (纸本)9798331505462

Public speaking plays an important role in various domains and most of the people struggle with it due to lack of experience and fear. To address this issue, we propose to develop a comprehensive public speaking model that aimed to help users to improve their presentation skills. Leveraging with new technologies such as deep learning or NLP, our model will provide real-time recording and analysis of presentations, to give customized feedback on speech rate, emotional expressions, and delivered content. By integrating speech recognition and facial emotion recognition module, the model aims to offer whole idea to users to enhance their communication skills. With this model, we target to empower people to overcome their public speaking apprehensions and become confident and proficient in speaking. © 2024 IEEE.

关键词： Emotion Recognition

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A Fuzzy Approach Towards the Measurement of Subject-Specific Cognitive Load during Mental Task Using Hemodynamic Response 4

A Fuzzy Approach Towards the Measurement of Subject-Specific...

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4th IEEE International Conference on Emerging Techniques in Computational Intelligence, ICETCI 2024

作者： Karmakar, Subashis Pal, Tandra Koley, Chiranjib National Institute of Technology Durgapur Department of Computer Science and Engineering West Bengal India National Institute of Technology Durgapur Department of Electrical Engineering West Bengal India

ISBN: (纸本)9798350387063

Every individual exhibits a different cognitive load for a particular task of the same level of difficulty. Measuring the cognitive load of an individual can help to develop an effective learning environment, design personalized learning materials and diagnose specific learning impairments. The primary aim of this study is to measure the subject-specific utilization of cognitive load during the mental arithmetic task using functional near-infrared spectroscopy (fNIRS) signals. For this purpose, we have collected fNIRS signals from fourteen healthy subjects while performing mental arithmetic tasks of three difficulty levels: low, medium and high. Statistical features are extracted from the collected fNIRS signal. After that, a fuzzy classifier has been developed where the fuzzy membership functions for each of the input features are generated using fuzzy c-means clustering. The experimental results show that the subjects undergoing the experiment utilize different levels of cognitive loads for a given task with the same level of difficulty. The proposed model achieves 89.92 % classification accuracy. © 2024 IEEE.

关键词： Near infrared spectroscopy

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Exploring Twitter Sentiments for Predicting Match Outcomes in the Game of Cricket 2

Exploring Twitter Sentiments for Predicting Match Outcomes i...

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2nd International Conference on Machine Learning and Data engineering, ICMLDE 2023

作者： Sharma, Karan Hota, Lopamudra Tikkiwal, Vinay Anand Kumar, Arun Department of Computer Science and Engineering National Institute of Technology Rourkela769008 India Department of Electronics and Communication Engineering Jaypee Institute of Information Technology Noida201304 India

In recent years, social media platforms such as Twitter have become popular among fans to discuss and share their opinions about the matches. This research aims to contribute to the growing body of knowledge on utilizing the sentiments expressed through messages on social media platforms to predict outcomes of matches in the sport of cricket. This research work provides insights into the effectiveness of sentiment analysis techniques in forecasting match outcomes, which can be beneficial to cricket fans, and cricket analysts. In this work, sentiment analysis is carried out based on models developed using various machine-learning techniques. The work also explores the impact of different features, such as the number of tweets collected, the timing of tweets, and the sentiment analysis techniques on the accuracy of the prediction. The results of this study have implications for cricket fans, sports analysts, and the broader field of predictive analytics. © 2024 Elsevier B.V.. All rights reserved.

关键词： Sentiment analysis

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Cross-Domain Collaborative Filtering: A Deep Neural Network Approach for Accurate and Diverse Recommendations 2

Cross-Domain Collaborative Filtering: A Deep Neural Network ...

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2nd International Conference on Machine Learning and Data engineering, ICMLDE 2023

作者： Goel, Chirag Sinha, Bam Bahadur Department of Computer Science and Engineering Indian Institute of Information Technology Jharkhand Ranchi834010 India

The rapid proliferation of data and the intricate nature of user behavior in the online realm have presented new hurdles for recommendation systems, which aim to suggest pertinent items to users. Among the notable challenges, ensuring the provision of accurate recommendations across diverse domains stands out. This research paper proposes an innovative solution to tackle this challenge by developing a cross-domain recommendation system that leverages the collaborative filtering technique to generate precise and varied recommendations spanning multiple domains. The system gathers user behavior and item attribute data from various domains and employs a collaborative filtering algorithm integrated with a deep neural network. The model makes use of a Neural Network with CReLU activation along with the embeddings of the user and the item followed by concealed layers. The output layer employs tanh activation to guarantee that recommendations fall within [-1, 1]. Adam optimizer, MSE loss, and an accuracy metric are utilised in training. This architecture captures user-item interactions effectively, resulting in precise personalised recommendations resulting an accuracy of 96.5% - 97.5%. To validate the effectiveness of the model, extensive evaluations are conducted on real-world datasets encompassing movies and books. The results demonstrate that the proposed system outperforms state-of-the-art recommendation systems in terms of accuracy, as measured by precision(89%), recall(90%), and AUC(0.74) scores. Furthermore, the system exhibits robust performance even in scenarios characterized by cold-start problems and data sparsity. © 2024 Elsevier B.V.. All rights reserved.

关键词： Collaborative filtering

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Data Analysis on Determining False Movie Ratings

Data Analysis on Determining False Movie Ratings

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Congress on Control, Robotics, and Mechatronics, CRM 2023

作者： Sahni, Ridhika Arockiasamy, Karmel School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Chennai600127 India

ISBN: (纸本)9789819955206

Online movie ratings have evolved into a serious business. Hollywood generates around $10 billion in box office revenue in the United States each year, and online ratings aggregators may have an increasing influence over where that money goes. A single film critic can no longer make or break a film, but perhaps thousands of critics, both professional and amateur, can how well can these platforms be trusted especially if they are showing the ratings and making money by selling the tickets? Do they have a bias by rating movies higher than it should be? The objective of the analysis is to provide brief research of one such online movie-ticket selling company, Fandango. The data collected from Fandango are analyzed and compared with the data collected from sites like Rotten Tomatoes, IMDB, and Metacritic. With the help of visualization, fraud and risk can be reduced offered by such online sites. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Visualization

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Recognition of mortar pumpability via computer vision and deep learning

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Journal of Electronic science and technology 2023年第3期21卷 73-81页

作者： Hao-Zhe Feng Hong-Yang Yu Wen-Yong Wang Wen-Xuan Wang Ming-Qian Du Research Institute Electronic Science and Technology University of Electronic Science and Technology of ChinaChengdu611731China School of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengdu611731China The Second Research Institute of Civil Aviation Administration of China Chengdu610041China

The mortar pumpability is essential in the construction industry,which requires much labor to estimate manually and always causes material *** paper proposes an effective method by combining a 3-dimensional convolutional neural network(3D CNN)with a 2-dimensional convolutional long short-term memory network(ConvLSTM2D)to automatically classify the mortar *** results show that the proposed model has an accuracy rate of 100%with a fast convergence speed,based on the dataset organized by collecting the corresponding mortar image *** work demonstrates the feasibility of using computer vision and deep learning for mortar pumpability classification.

关键词： Classification computer vision Deep learning Pumpability 2-dimensional convolutional long short-term memory network (ConvLSTM2D) 3-dimensional convolutional neural network(3D CNN)

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Deep Learning-Based Intelligent GUI Tool For Skin Disease Diagnosis System 5th

Deep Learning-Based Intelligent GUI Tool For Skin Disease Di...

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5th International Conference on Computational Intelligence in Communications and Business Analytics, CICBA 2023

作者： Karmakar, Mithun Mondal, Subhash Nag, Amitava Computer Science and Engineering Central Institute of Technology Kokrajhar BTR Assam Kokrajhar783370 India

ISBN: (纸本)9783031488757

Skin diseases are generally normal around the globe, as people get skin diseases because of inheritance and natural elements. Dermatologists rely heavily on visual examinations to diagnose skin diseases. However, this method can be inaccurate and time-consuming. The development of the technique in deep learning (DL) and the availability of GPUs can expand and improve the quality of computer-aided disease diagnostics systems. This paper proposes a DL-based smartphone application to aid a dermatologist in diagnosing skin disease in real-time. In the proposed work, we first used fine-tuned DenseNet201 for feature extraction and SVM to accurately classify normal and abnormal skin. A Deep Ensemble CNN (DECNN) framework with DenseNet-201, Resnet50, and MobileNet is further used for skin disease categorization if abnormal skin is detected. The experimental outcome of this study demonstrates that the framework can achieve an 84% accuracy in skin disease classification and outperform existing state-of-the-art works. The simple implementation and acceptable accuracy of the proposed method can be helpful for dermatologists in the diagnosis of skin disease. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Convolution

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Utilization of UAVs to Detect and Locate Safe Sites in Disaster Affected Area Using Geo-Referencing 2

Utilization of UAVs to Detect and Locate Safe Sites in Disas...

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2nd International Conference on Emerging Trends in Information technology and engineering, ic-ETITE 2024

作者： Garg, Rishi Srivastava, Ritik Rathore, Vishakha Gautam, Sanjay Kumar Gupta, Amit Saha, Prasannam Kumar Kumar, J. Sathish Motilal Nehru National Institute of Technology Allahabad Computer Science and Engineering Department Prayagraj India

ISBN: (纸本)9798350328202

Over the years the change in global climatic conditions, like the greenhouse effect, and global warming have led to sudden increases in natural disasters mostly weather, climates, and water extremes. which has led to the loss of lives, and resources and affected the economies adversely. While on the one hand the efforts to prevent disasters and the natural habitat of the earth are continued, we have to also be prepared for sudden cases. As much as the prediction of disaster is important in planning rescue missions, the post-disaster process and planning are also crucial, which actually decide the impact of the disaster. In this paper, our approach lies in the post-disaster Response phase, where we take immediate actions after the disaster hits. Drones will be used to access the site and find some safe spots in the affected area which can be used by the rescue team to build safe sites, store goods, accumulate hostiles, or shape their rescue mission in many ways. © 2024 IEEE.

关键词： computer vision

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