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检索条件"机构=Department of Computer Engineering and Computer Science"
387424 条 记 录,以下是4671-4680 订阅
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Automated Bone Fracture Detection using YOLOv8
Automated Bone Fracture Detection using YOLOv8
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Disruptive Technologies (ICDT), International Conference on
作者: Priyanshu Agarwal Pushpendra Kumar Department of Computer Science and Engineering KIET Group of Institutions Ghaziabad India
In medical diagnostics, detection of bone fracture is very crucial. It require time and accurate treatment of that injuries. Previous methods for bone fracture detection are X-ray in which analyzes the fracture by the... 详细信息
来源: 评论
Building Secure and Decentralized Survey Methodology: A Comprehensive Solution with FIDO2 Authentication and Fluree
Building Secure and Decentralized Survey Methodology: A Comp...
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International Conference on Communication Systems and Network Technologies (CSNT)
作者: Jawahar Balachandher Chandana Dongre Somanshu Bhattacharyya Rohit Hunashikatti Sarasvathi V Department of Computer Science and Engineering PES University Bangalore Karnataka India
Traditional survey systems struggle with data immutability, privacy protection, and reliable storage. These limitations compromise transparency, security, and data integrity. This paper proposes a decentralized and se... 详细信息
来源: 评论
On the Role of Adversarial Perturbations in Unsupervised Deep Learning for Enhancing Image Quality of Degraded Medical-Images
On the Role of Adversarial Perturbations in Unsupervised Dee...
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IEEE International Symposium on Biomedical Imaging
作者: Vatsala Sharma Ashwin Goyal Suyash P. Awate Computer Science and Engineering Department Indian Institute of Technology Bombay Mumbai
Unsupervised learning enables deep-neural-network (DNN) training without high-quality data. Typical DNN methods for unsupervised image quality enhancement either (i) focus only on spatially uncorrelated noise, (ii) de... 详细信息
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Advancements and Challenges in Quantum Machine Learning for Medical Image Classification: A Comprehensive Review
Advancements and Challenges in Quantum Machine Learning for ...
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International Symposium on Advanced Computing and Communication (ISACC)
作者: Md. Farhan Shahriyar Gazi Tanbhir Department of Computer Science and Engineering World University of Bangladesh Dhaka Bangladesh
Quantum technologies are rapidly advancing as image classification tasks grow more complex due to large image volumes and extensive parameter updates required by traditional machine learning models. Quantum Machine Le... 详细信息
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A Review of Generative AI in Recommendation Systems
A Review of Generative AI in Recommendation Systems
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Data science, Agents & Artificial Intelligence (ICDSAAI), International Conference on
作者: Shivaani V P Muthupandi G S. Pavithra Department of Computer Science and Engineering Chennai Institute of Technology Chennai Tamilnadu
Traditional machine learning algorithms have paved the way for more sophisticated models mainly in the field of Gen AI. This review compares how Gen AI is used in recommendation systems to traditional AI methods and t... 详细信息
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Semi-Supervised Learning Approach Using Hybrid Bidirectional LSTM Networks for Diabetes Prediction with Explainable AI
Semi-Supervised Learning Approach Using Hybrid Bidirectional...
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International Conference on Electrical, computer and Communication engineering (ECCE)
作者: Md Shahadat Kabir Tanvir Azhar Department of Computer Science & Engineering East Delta University Chattogram Bangladesh
Diabetes is a serious health condition that can result in serious complications if not properly detected or treated. Despite recent developments in machine learning and deep learning, which have enhanced the detection... 详细信息
来源: 评论
Linguistic Analysis of Sinhala YouTube Comments on Sinhala Music Videos: A Dataset Study
arXiv
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arXiv 2025年
作者: De Mel, W.M. Yomal de Silva, Nisansa Department of Computer Science & Engineering University of Moratuwa Moratuwa Sri Lanka
This research investigates the area of Music Information Retrieval (MIR) and Music Emotion Recognition (MER) in relation to Sinhala songs, an underexplored field in music studies. The purpose of this study is to analy... 详细信息
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InteractNet: Improved Drug-Drug Interaction Prediction in Pharmacology Using Deep Neural Networks  18th
InteractNet: Improved Drug-Drug Interaction Prediction in P...
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18th International Conference on Practical Applications of Computational Biology and Bioinformatics, PACBB 2024
作者: Chaurasia, Anushka Kumar, Deepak Yogita, Yogita Department of Computer Science and Engineering National Institute of Technology Meghalaya Shillong India Department of Computer Engineering National Institute of Technology Kurukshetra Kurukshetra India
In the context of modern medicine, where polypharmacy is prevalent, particularly among older adults, the potential for hazardous drug-drug interactions (DDIs) is a significant concern. These interactions can lead to s... 详细信息
来源: 评论
Ranking Comments for Bug Reports Using Deep Learning  29th
Ranking Comments for Bug Reports Using Deep Learning
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29th International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2024
作者: Chang, Ching-Hsiang Lu, Liang-Chen Yang, Cheng-Zen Department of Computer Science and Engineering Yuan Ze University Taoyuan Taiwan
Important bug report comments can help developers efficiently fix bugs. This paper proposes a bug report comment ranking model called BRCR based on deep learning models. This paper also proposes a pseudo-labeling appr... 详细信息
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Social Media Analysis for Criminal Behavior Detection: Methods, Application and Challenge
Social Media Analysis for Criminal Behavior Detection: Metho...
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Sentiment Analysis and Deep Learning (ICSADL), International Conference on
作者: Prachi Patel Kush Bhushanwar Hemlata Patel Computer Engineering Department PIET Parul University Vadodara Gujarat India Computer Science & Engineering Department PIET Parul University Vadodara Gujarat India
Social media websites have provided rich contextual data but its misuse for criminal activities creates lot of problems. This paper seeks to solve the problem of criminal behavioral analysis on social media platforms ... 详细信息
来源: 评论