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共 67328 条记录，以下是461-470 订阅

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Systematic Analysis of Underwater Image Dehazing and Object Detection 6

Systematic Analysis of Underwater Image Dehazing and Object ...

引用

6th Asia Symposium on Image Processing, ASIP 2024

作者： Ghei, Anushka Krishnan, Dhriti Rajesh Santhosh, Gautam Natarajan, S. PES University Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350376159

Dehazing underwater images is crucial for several underwater applications, including marine biology, exploration, and monitoring. Because of colour distortion, light attenuation, and scattering, underwater imaging presents particular difficulties. This research presents a systematic survey on using transformers and different Generative Adversarial Networks (GANs) for dehazing underwater photos. This survey study looks into transformer-based models, analyzes GAN designs (CycleGAN, Pix2Pix, and UWGAN) in detail, and compares them using a range of metrics, such as Mean Squared Error (MSE), Structural Similarity Index Measure (SSIM), Frechet Inception Distance (FID), and F1-score. Further analysis was carried out using CLAHE on the best-performing models. Our findings emphasize the benefits and drawbacks of the different designs that were employed as well as prospective directions for further study and advancement. © 2024 IEEE.

关键词： Underwater photography

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Deep Dive into Predictive Modeling for Autism Spectrum Disorder using Facial Features and Machine Learning

Deep Dive into Predictive Modeling for Autism Spectrum Disor...

引用

2024 International Conference on Communication, Computing and Internet of Things, IC3IoT 2024

作者： Bhat, Chaitra Goutham, Gagan Bannur, Charvi Kakarla, Sada Mamatha, H.R. Pes University Dept. Of Computer Science & Engineering Bengaluru India

ISBN: (纸本)9798350352689

Autism Spectrum Disorder is a neuro-development behavioural disorder that is classified as a chronic disability leaving individuals unable to accurately grasp their environment and can lead to limited development of communication skills, thinking and other social skills. Prediction of ASD using video recordings is an open-ended critical problem in machine learning to facilitate the process of early intervention which requires high computational resources. This research aims to predict ASD in children using videos by extracting features and converting them into a binary classification problem thereby eliminating the need for high computational resources. This research postulates a study of machine learning techniques like Logistic Regression, Decision Trees and Neural Networks in comparison for the prediction of ASD as well as a novel approach to reduce the computational requirements for the analysis of videos. This research also addresses the lack of publically available video datasets for the analysis of Autism. The highest accuracy metric for the models was using the Neural Network architecture closely followed by the Decision Tree Classifier which yielded accuracies of 99.8% and 99.65% respectively. In this article, we offer an overview of predicting Autism Spectrum Disorder whilst focusing on the importance of video datasets. © 2024 IEEE.

关键词： Forecasting

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A Single-Weight Neural Network for MIMO Signal Detection: Algorithm and Implementation 10

A Single-Weight Neural Network for MIMO Signal Detection: Al...

引用

10th International Conference on engineering and Emerging Technologies, ICEET 2024

作者： Ho, Yi-Cheng Yen, Mao-Hsu Lu, Hoang-Yang National Taiwan Ocean University Dept. of Computer Science and Engineering Keelung Taiwan National Taiwan Ocean University Dept. of Electrical and Engineering Keelung Taiwan

ISBN: (纸本)9798331532895

Existing deep learning-based MIMO detectors often face substantial memory demands due to the need to store neural network weights, posing a significant challenge to practical implementation. To address this issue, we propose a single-weight neural network, namely SW-Net. By reducing each layer's weight vector to a scalar, the required hardware storage is significantly reduced. Simulation results demonstrate that hardware requirements can be reduced while maintaining bit error rate (BER) performance. Additionally, we present the corresponding VLSI hardware architecture, implemented using TSMC's 90-nm CMOS technology, operating at 707 MHz. This design requires 1109 kGEs and achieves a throughput of 707 Mbps. © 2024 IEEE.

关键词： Deep neural networks

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Preprocessing and Feature Extraction based Deepfake Detection on Combined dataset 2

Preprocessing and Feature Extraction based Deepfake Detectio...

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2nd IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation, IATMSI 2024

作者： Thejas, N.U. Nayak, Hithesh D. Siddique, Abbu Bucker Anas Danish, Mohammed Mamatha, H.R. Pes University Computer Science & Engineering Dept. Bengaluru India

ISBN: (纸本)9798350360523

There are many deepfake detection models available, each with their own limitations. This research concentrates on one such limitation and addresses it. That research gap would be the inefficient behavior of the deepfake detection model on the orientation of faces in the input image or video. The architecture starts by combining the data sets of DFDC, Celeb-DF, and Face Forensics++. Then frame-extraction and pre-processing on the frames take place. The next stage is crucial and differs from other models;it is the feature extraction stage, where specific face-orientation-related features are extracted from each frame. The features that are extracted are a histogram of oriented gradients, local binary patterns, and scale-invariant feature transforms. Later on in the architecture, normalization of features happens in independent neural network pipelines. Then features are combined and passed onto the next neural network, which will classify the videos as deepfake or not. The validation accuracy of this architecture is 95.89%. © 2024 IEEE.

关键词： Feature extraction

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Machine Learning Techniques in Epileptic Seizure Detection: A Comprehensive Review 15

Machine Learning Techniques in Epileptic Seizure Detection: ...

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Thakare, Vishal Ranawat, Rekha Sage University Dept. of computer Science and Engineering Indore India

ISBN: (纸本)9798350370249

The neurological disorder known as epilepsy is defined by its recurrent, spontaneous episodes of seizures impacting millions of people globally. The timely and accurate detection of epileptic seizures is necessary for a successful administration and ensuring patient safety. In recent times, techniques using machine learning have emerged as promising solutions to automate the detection of seizures. This review paper presents a thorough overview of the latest advancements in the identification of epileptic seizures through the application of machine learning, encompassing data sources, extraction of features, application of classification algorithms, use of performance evaluation metrics, addressing various challenges, and future directions. In addition, we put forth a novel methodology in order to enhance seizure detection accuracy by integrating the models of deep learning. Our approach uses multiple modalities for seizure prediction with cross-model training to mitigate data scarcity. Through a rigorous analysis of existing literature and our proposed methodology, this paper provides insightful information for practitioners and researchers looking into the detection of epileptic seizures. © 2024 IEEE.

关键词： deep learning Epilepsy epileptic seizures Machine learning neurological Seizures

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Call Translator with Voice Cloning Using Transformers 9

Call Translator with Voice Cloning Using Transformers

引用

9th IEEE International Conference for Convergence in Technology, I2CT 2024

作者： Khan, Nawaz Fateen Hemanth, Nandan Goyal, Navyae Pranav, K.R. Agarwal, Pooja Pes University Computer Science Engineering Dept. Bangalore India

ISBN: (纸本)9798350394474

Voice Cloning employs technology and algorithms to create an artificial or synthetic reproduction of a person's voice. To understand and mimic the distinct vocal qualities of the target speaker, including tone, pitch, cadence, and pronunciation, a machine learning model must be trained on audio samples of the speaker. This project presents itself as a revolutionary approach to the enduring problem of successful cross-lingual interactions, the paper's novel approach to speech-to-speech machine translation that incorporates voice cloning. This method allows us to synthesize speech in the target language while maintaining the original speaker's vocal characteristics. The model algorithms such as Whisper AI(WER 5% for transcription, No-Language-Left-Behind-200(44% more accurate than other models) for translation, Tacotron for speech synthesis and multiple transformers for voice cloning will be incorporated. The Voice Cloning model operates effectively on unseen voices, transcending the limitations of voice cloning will be incorporated. The voice cloning model operates effectively on unseen voices, transcending the limitations of relying solely on pre-trained models. The model successfully clones users' voices in a different language with an approximate latency of 10 seconds. © 2024 IEEE.

关键词： Speech synthesis

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A Secure method of transferring confidential documents by leveraging Zero Trust Principles and Blockchain Technology 4

A Secure method of transferring confidential documents by le...

引用

4th IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2024

作者： Alex, Hannah Thankam Alex, Sarah Swathi, C.G. Chavan, Chandrashekhar Pomu Pes University Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798331518981

Ensuring regulatory compliance and maintaining client trust in the legal industry depend on the safe transfer and preservation of sensitive data. Maintaining the safety and security of confidential information is essential in a law business. The suggested concept combines zero-trust concepts with blockchain technology to develop a decentralized application (dApp) that facilitates secure document sharing between clients and law firms. To guarantee the safe transfer of private legal documents, the platform makes use of IPFS for decentralized file storage and MetaMask for authentication. OTP verification, document encryption using cryptographic methods, and MetaMask user authentication are some of its key features. Only authorized users are able to view or manage documents in the DApp thanks to smart contract access management. The requirements for security, immutability, and transparency are maintained by this method. © 2024 IEEE.

关键词： Smart contract

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Real-Time Performance Verification of a Commercial Transformer Differential Relay under GIC Conditions 4

Real-Time Performance Verification of a Commercial Transform...

引用

4th Annual IEEE Kansas Power and Energy Conference, KPEC 2023

作者： Ahmadzadeh-Shooshtari, Babak Rezaei-Zare, Afshin York University Dept. of Electrical Engineering and Computer Science Toronto Canada

ISBN: (纸本)9798350335408

Transformer differential protection employs a harmonic blocking (HB) function that blocks the relay operation when harmonic levels, specifically second harmonics, in transformer differential currents are high. Such a condition can occur when a transformer experiences part-cycle core saturation caused by geomagnetically induced current (GIC). Offline studies on transformer differential relays in the literature show that these relays are likely to remain blocked by the HB function for in-zone faults during the GIC. In this paper, hardware-in-the-loop (HIL) tests are conducted to analyze the response of a commercial differential relay to the faults during the GIC. The experimental results show that the relay fails to operate for in-zone faults during the GIC, regardless of the configuration of the employed HB function. This study concludes that the performance of the existing commercial relays should be experimentally verified and proposes a solution to immunize the transformer protection schemes against GIC consequences. © 2023 IEEE.

关键词： Relay protection

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RPC Relay protocol for NaaS platforms 2

RPC Relay protocol for NaaS platforms

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2nd IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation, IATMSI 2024

作者： Anirudh, R.H. Darshan, V. Dey, Kohav Phaneesh, S. Jadon, Shruti Pes University Computer Science & Engineering Dept. Bengaluru India

ISBN: (纸本)9798350360523

The decentralized internet, often termed as Web3, is envisioned as the future of the online world. It holds the promise of addressing the centralization and censorship issues prevalent in today's web landscape. Yet, a significant hurdle faced by Web3 is its reliance on centralized servers provided by major entities like AWS and Azure. The vulnerability of this reliance becomes apparent when these servers encounter downtime or other disruptions, potentially causing widespread issues. This paper focuses on the crucial necessity of decentralizing Web3's infrastructure to bolster its resilience against such outages. To accomplish this objective, we introduce an innovative RPC (Remote Procedure Call) relay protocol tailored specifically for Web3. This protocol not only caters to the requirements of Network as a Service (NaaS) platforms but also introduces incentives to motivate network nodes to function as relays. Our research and development efforts focus on two fundamental aspects: first, the technical implementation of the RPC relay protocol, and second, the incentivization mechanisms that reward network nodes for participating as relays. By enabling a more decentralized and robust infrastructure, we aim to enhance the reliability and stability of Web3 services. © 2024 IEEE.

关键词： Blockchain

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Intelligent Resource Allocation for RIS-Assisted Cell-Free Massive MIMO Systems 22

Intelligent Resource Allocation for RIS-Assisted Cell-Free M...

引用

22nd IEEE Consumer Communications and Networking Conference, CCNC 2025

作者： Mollah, Gloria Haider, Majumder Rawat, Danda B. Ahmed, Imtiaz Howard University Dept. of Electrical Engineering & Computer Science WashingtonDC United States

ISBN: (纸本)9798331508050

Cell-free massive multiple-input multiple-output (mMIMO) systems distribute a large number of access points (APs) over a wide geographic region, improving coverage, capacity, and user experiences notably. Similarly, reconfigurable intelligent surface (RIS) allows a significant leap forward in signal quality and energy efficiency by adding additional flexibility and intelligent control over the propagation environment of wireless systems. However, optimal resource allocation in RIS-integrated cell-free mMIMO systems faces substantial challenges due to the presence of a large number of APs and passive reflecting elements (PREs) at RIS while simultaneously providing network coverage to aerial and ground users. To efficiently navigate the high-dimensional optimization space, this paper proposes a novel framework for optimal resource allocation in RIS-assisted cell-free mMIMO systems employing deep learning (DL) techniques. In particular, we train a deep neural network offline to optimize the transmit powers at APs and the phase shift of PREs at RIS. The trained model is tested online to perform real-time optimization with low computational complexity. Simulation results demonstrate the effectiveness of the proposed data-driven resource allocation scheme while comparing it with the state-of-the-art baseline scheme. © 2025 IEEE.

关键词： Deep neural networks

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