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Recent Advancements of Computer Vision in Healthcare: A Systematic Review

IEIE Transactions on Smart Processing and Computing 2024年第6期13卷 563-571页

作者： Islam, Mahmudul Nayan, Nasim Mahmud Islam, Ashraful Sikder, Sankar Rashel, Masud Rana Alam, Md. Zahangir Department of Computer Science and Engineering Independent University Bangladesh Dhaka1229 Bangladesh Center for Computational & Data Sciences Independent University Bangladesh Dhaka1229 Bangladesh Department of Mathematics University of Louisiana LafayetteLA70503 United States Department of Mechatronics Engineering University of Évora Évora Portugal

The advancements in Computer Vision (CV) techniques have demonstrated significant promise in healthcare applications. The adoption of CV within the healthcare sector has drawn considerable attention. The aim of this study is to systematically review and synthesize the recent advancements and applications of CV techniques in various domains of healthcare. 125 papers were selected initially, and after gradual filtering, 20 papers were selected for the final study. In this study, we have identified five medical domains such as disease detection, drug discovery, surgical procedures, human identity decoding, and remote patient monitoring where CV applications are being successfully implemented. Among these domains, the use of CV in surgical assistance is notable. It capitalizes on the precision and efficiency offered by CV. Deep Learning (DL) models show adaptability and accuracy in medical imaging. The combination of computer vision and sensors enhances real-time surgical skills assessment. This study revealed that CV applications can be utilized for predictive analytics and personalized patient treatments. Standardized performance metrics, ethics, and data governance are crucial for responsible computer vision deployment in healthcare. Copyrights © 2024 The Institute of Electronics and Information Engineers.

关键词： Deep learning

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Few-shot Prompting for Pairwise Ranking: An Effective Non-Parametric Retrieval Model

Few-shot Prompting for Pairwise Ranking: An Effective Non-Pa...

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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Sinhababu, Nilanjan Parry, Andrew Ganguly, Debasis Samanta, Debasis Mitra, Pabitra Centre for Computational and Data Sciences IIT Kharagpur India School of Computing Science University of Glasgow United Kingdom Department of Computer Science and Engineering IIT Kharagpur India

ISBN: (纸本)9798891761681

A supervised ranking model, despite its effectiveness over traditional approaches, usually involves complex processing - typically multiple stages of task-specific pre-training and fine-tuning. This has motivated researchers to explore simpler pipelines leveraging large language models (LLMs) that can work in a zero-shot manner. However, since zero-shot inference does not make use of a training set of pairs of queries and their relevant documents, its performance is mostly worse than that of supervised models, which are trained on such example pairs. Motivated by the existing findings that training examples generally improve zero-shot performance, in our work, we explore if this also applies to ranking models. More specifically, given a query and a pair of documents, the preference prediction task is improved by augmenting examples of preferences for similar queries from a training set. Our proposed pairwise few-shot ranker demonstrates consistent improvements over the zero-shot baseline on both in-domain (TREC DL) and out-domain (BEIR subset) retrieval benchmarks. Our method also achieves a close performance to that of a supervised model without requiring any complex training pipeline. © 2024 Association for computational Linguistics.

关键词： computational linguistics

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Secured and Privacy-Preserving GPU-Based Machine Learning Inference in Trusted Execution Environment: A Comprehensive Survey 17

Secured and Privacy-Preserving GPU-Based Machine Learning In...

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17th International Conference on COMmunication Systems and NETworkS, COMSNETS 2025

作者： Chaudhuri, Arunava Shukla, Shubhi Bhattacharya, Sarani Mukhopadhyay, Debdeep Indian Institute of Technology Kharagpur Department of Computer Science and Engineering Kharagpur India Indian Institute of Technology Kharagpur Centre for Computational and Data Sciences Kharagpur India

ISBN: (纸本)9798331531195

With the rapid advancement of machine learning (ML) models and their widespread application across various sectors such as intrusion detection, medical diagnosis, natural language processing, and autonomous driving, these technologies have achieved remarkable success. However, this progress has also raised significant concerns about ensuring the security of ML models and protecting both private training data and model outputs from getting exposed in a shared cloud environment. To address these challenges, researchers have proposed various methodologies to create privacy-preserving, secure, and trustworthy model execution environments to prevent adversarial attacks. This study provides a comprehensive review of Trusted Execution Environment (TEE) implementations across different hardware accelerators. It also offers an overview of modern techniques for preserving privacy and security in execution environments, while identifying critical research gaps that require attention. In essence, this survey is an important resource for researchers, providing insights into recent methodologies and guiding them to focus on pressing research challenges. © 2025 IEEE.

关键词： Adversarial machine learning

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Spectroscopy and molecule opacity investigation on excited states of SiS

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Chinese Physics B 2024年第5期33卷 381-387页

作者：李瑞吕浩男桑纪群刘晓华梁桂颖吴勇 College of Teacher Education Qiqihar UniversityQiqihar 161006China National Key Laboratory of Computational Physics Institute of Applied Physics and Computational MathematicsBeijing 100088China Department of Physics College of ScienceQiqihar UniversityQiqihar 161006China School of Data Science and Artificial Intelligence Jilin Engineering Normal UniversityChangchun 130052China HEDPS Center for Applied Physics and TechnologyPeking UniversityBeijing 100084China

The SiS molecule,which plays a significant role in space,has attracted a great deal of attention for many *** to complex interactions among its low-lying electronic states,precise information regarding the molecular structure of SiS is *** obtain accurate information about the structure of its excited states,the high-precision multireference configuration interaction(MRCI)method has been *** method is used to calculate the potential energy curves(PECs)of the 18Λ–S states corresponding to the lowest dissociation limit of *** core–valence correlation effect,Davidson’s correction and the scalar relativistic effect are also included to guarantee the precision of the MRCI *** on the calculated PECs,the spectroscopic constants of quasi-bound and bound electronic states are calculated and they are in accordance with previous experimental *** transition dipole moments(TDMs)and dipole moments(DMs)are determined by the MRCI *** addition,the abrupt variations of the DMs for the 1^(5)Σ^(+)and 2^(5)Σ^(+)states at the avoided crossing point are attributed to the variation of the electronic *** opacity of SiS at a pressure of 100 atms is presented across a series of *** increasing temperature,the expanding population of excited states blurs the band boundaries.

关键词： SiS opacity excited state spectroscopic constant configuration interaction

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GAN‐MD:A myocarditis detection using multi‐channel convolutional neural networks and generative adversarial network‐based data augmentation

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CAAI Transactions on Intelligence Technology 2024年第4期9卷 866-878页

作者： Hengame Ahmadi Golilarz Alireza Azadbar Roohallah Alizadehsani Juan Manuel Gorriz Department of Medical Radiation Engineering Faculty of EngineeringLahijan BranchIslamic Azad UniversityLahijanIran Department of Medical Radiation Engineering Lahijan BranchIslamic Azad UniversityLahijanIran Institute for Intelligent Systems Research and Innovation(IISRI) Deakin UniversityWaurn PondsVictoriaAustralia Data Science and Computational Intelligence Institute University of GranadaGranadaSpain

Myocarditis is a significant public health concern because of its potential to cause heart failure and sudden *** standard invasive diagnostic method,endomyocardial bi-opsy,is typically reserved for cases with severe complications,limiting its widespread ***,non‐invasive cardiac magnetic resonance(CMR)imaging presents a promising alternative for detecting and monitoring myocarditis,because of its high signal contrast that reveals myocardial *** assist medical professionals via artificial intelligence,the authors introduce generative adversarial networks‐multi discriminator(GAN‐MD),a deep learning model that uses binary classification to diagnose myocarditis from CMR *** approach employs a series of convolutional neural networks(CNNs)that extract and combine feature vectors for accurate *** authors suggest a novel technique for improving the classification precision of *** generative adversarial networks(GANs)to create synthetic images for data augmentation,the authors address challenges such as mode collapse and unstable *** a reconstruction loss into the GAN loss function requires the generator to produce images reflecting the discriminator features,thus enhancing the generated images'quality to more accurately replicate authentic data ***,combining this loss function with other reg-ularisation methods,such as gradient penalty,has proven to further improve the perfor-mance of diverse GAN models.A significant challenge in myocarditis diagnosis is the imbalance of classification,where one class dominates over the *** mitigate this,the authors introduce a focal loss‐based training method that effectively trains the model on the minority class *** GAN‐MD approach,evaluated on the Z‐Alizadeh Sani myocarditis dataset,achieves superior results(F‐measure 86.2%;geometric mean 91.0%)compared with other deep learning models and traditional machine learning methods.

关键词： 2‐D 3‐D

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Minimal Counters, Maximum Insight: Simplifying System Performance With HPC Clusters for Optimized Monitoring

IEEE Computer Architecture Letters

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IEEE Computer Architecture Letters 2025年第1期24卷 177-180页

作者： Shukla, Shubhi Singh, Abhijeet Chakraborty, Rajdeep Chakraborty, Anirban Rathod, Tejas Mumbaikar, Harshal Munigala, Manoj Kumar Madhusudhan, K.N. Mitra, Pabitra Mukhopadhyay, Debdeep Indian Institute of Technology Kharagpur Centre for Computational Data Sciences India Indian Institute of Technology Kharagpur Computer Science and Engineering Department India Intel Corporation Bangalore India

As computer systems become more complex, evaluating performance requires tracking various hardware performance counters that capture the system's internal activities. While these counters provide valuable insights, their growing number makes it challenging to identify the most relevant ones for performance analysis. In this paper, we investigate the correlation between performance counter values and overall system performance, while also exploring the inter-correlation between different counters. Our findings demonstrate that specific counters are strongly correlated with key performance metrics and that significant redundancy exists among counters. By leveraging these relationships, we propose a method for selecting a small, representative set of performance counters. This streamlined set can further be used to accurately predict performance score across various workloads and system configurations. © 2002-2011 IEEE.

关键词： Complex networks

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Fully-Decoupled and Second-Order Time-Accurate Scheme for the Cahn–Hilliard Ohta–Kawaski Phase-Field Model of Diblock Copolymer Melt Confined in Hele–Shaw Cell

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Communications in Mathematics and Statistics 2024年第3期12卷 479-504页

作者： Junying Cao Jun Zhang Xiaofeng Yang School of Data Science and Information Engineering Guizhou Minzu UniversityGuiyang 550025People’s Republic of China Guizhou Key Laboratory of Big Data Statistics Analysis Computational Mathematics Research CenterGuizhou University of Finance and EconomicsGuiyang 550025People’s Republic of China Department of Mathematics University of South CarolinaColumbiaSCUSA

In this work,we consider numerical approximations of the phase-field model of diblock copolymer melt confined in Hele–Shaw cell,which is a very complicated coupled nonlinear system consisting of the Darcy equations and the Cahn–Hilliard type equations with the Ohta–Kawaski *** the combination of a novel explicit-Invariant Energy Quadratization approach and the projection method,we develop the first full decoupling,energy stable,and second-order time-accurate numerical *** introduction of two auxiliary variables and the design of two auxiliary ODEs play a vital role in obtaining the full decoupling structure while maintaining energy *** scheme is also linear and unconditional energy stable,and the practical implementation efficiency is also very high because it only needs to solve a few elliptic equations with constant coefficients at each time *** strictly prove that the scheme satisfies the unconditional energy stability and give a detailed implementation *** experiments further verify the convergence rate,energy stability,and effectiveness of the developed algorithm.

关键词： Phase-field Explicit-IEQ Darcy Decoupled Energy Stability Diblock copolymer melt

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Detecting the symptoms of COVID-19 during pandemic environment using smart spectacle thermal images and deep capsule networks

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Multimedia Tools and Applications 2025年第8期84卷 4475-4501页

作者： Dwarakanath, B. Pandimurugan, V. Mohandas, R. Sambath, M. Baiju, B.V. Chinnasamy, A. SRM Institute of Science and Technology Ramapuram Chennai India Networking and Communications School of Computing SRMIST kattankulathur Chennai India Computational Intelligence School of Computing SRMIST kattankulathur Chennai India Computer Science and Engineering Hindustan Institute of Technology and Science Chennai India School of Computer Science and Engineering Vellore Institute of Technology Vellore India Department of Data Science and Business Systems School of Computing SRMIST kattankulathur Chennai India

The pandemic creates a more complicated providence of medical assistance and diagnosis procedures. In the world, Covid-19, Severe Acute Respiratory Syndrome Coronavirus-2 (SARS Cov-2), and plague are widely known pandemic disease desperations. Due to the recent COVID-19 pandemic tragedies, various medical diagnosis models and intelligent computing solutions are proposed for medical applications. In this era of computer-based medical environment, conventional clinical solutions are surpassed by many Machine Learning and Deep Learning-based COVID-19 diagnosis models. Anyhow, many existing models are developing lab-based diagnosis environments. Notably, the Gated Recurrent Unit-based Respiratory data Analysis (GRU-RE), Intelligent Unmanned Aerial Vehicle-based Covid data Analysis (Thermal Images) (I-UVAC), and Convolutional Neural Network-based Computer Tomography Image Analysis (CNN-CT) are enriched with lightweight image data analysis techniques for obtaining mass pandemic data at real-time conditions. However, the existing models directly deal with bulk images (thermal data and respiratory data) to diagnose the symptoms of COVID-19. Against these works, the proposed spectacle thermal image data analysis model creates an easy and effective way of disease diagnosis deployment strategies. Particularly, the mass detection of disease symptoms needs a more lightweight equipment setup. In this proposed model, each patient's thermal data is collected via the spectacles of medical staff, and the data are analyzed with the help of a complex set of capsule network functions. Comparatively, the conventional capsule network functions are enriched in this proposed model using adequate sampling and data reduction solutions. In this way, the proposed model works effectively for mass thermal data diagnosis applications. In the experimental platform, the proposed and existing models are analyzed in various dimensions (metrics). The comparative results obtained in the experiments just

关键词： COVID-19

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Unusual metallic state in superconducting A15-type La4H23

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National science Review 2024年第12期11卷 94-103页

作者： Jianning Guo Dmitrii Semenok Grigoriy Shutov Di Zhou Su Chen Yulong Wang Kexin Zhang Xinyue Wu Sven Luther Toni Helm Xiaoli Huang Tian Cui State Key Laboratory of Superhard Materials College of Physics Jilin University Center for High Pressure Science and Technology Advanced Research (HPSTAR) Department of High-Temperature Superconductivity Skolkovo Institute of Science and Technology Skolkovo Innovation CenterComputational and Data Science and Engineering HochfeldMagnetlabor Dresden(HLD-EMFL) and Würzburg-Dresden Cluster of Excellence Helmholtz-Zentrum Dresden-Rossendorf(HZDR) School of Physical Science and Technology Ningbo University

Hydride superconductors continue to fascinate the communities of condensed matter physics and material scientists because they host the promising near room-temperature superconductivity. Current research has concentrated on the new hydride superconductors with the enhancement of the superconducting transition temperature（Tc）. The multiple extreme conditions（high pressure/temperature and magnetic field） will introduce new insights into hydride superconductors. The study of transport properties under very high magnetic fields facilitates the understanding of superconductivity in conventional hydride *** the present work, we report experimental evidence of an unusual metal state in a newly synthesized cubic A15-type La4H23that exhibits superconductivity with a Tc reaching 105 K at 118 GPa. A large negative magnetoresistance is observed in strong pulsed magnetic fields in the non-superconducting state of this compound below 40 K. Moreover, we construct the full magnetic phase diagram of La4H23up to 68 T at high pressure. The present work reveals anomalous electronic structural properties of A15-La4H23under high magnetic fields, and therefore has great importance with regard to advancing the understanding of quantum transport behaviors in hydride superconductors.

关键词： high-pressure superconductivity hydrides negative magnetoresistance

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Augmented Reality and Artificial Intelligence in Sign Language Expression 3

Augmented Reality and Artificial Intelligence in Sign Langua...

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3rd IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing, INCOS 2024

作者： Kaviyaraj, R. Sathya, P. Nandhini, P. Vinoth Kumar, P. Chelliah, Sureshkumar Ezhilmathi, S. Srm Institute of Science and Technology Department of Computational Intelligence Kattankulathur India Sri Shanmuga Collage of Engineering and Technology Department of Computer Science and Engineering Sankari India St. Joseph's Institute of Technology Omr Department of Artificial Intelligence and Data Science Chennai India

ISBN: (纸本)9798350361186

Sign language, the vibrant tapestry of hand gestures and facial expressions, is the lifeblood of Deaf and hardof-hearing communities. For millions of signers, American Sign Language (ASL) runs deeper than communication, fundamental to identity, expression, and belonging. And yet an unshakeable communication gap leaves users of ASL frequently marooned away from the hearing world, kept from education, healthcare, or employment, or from basic, everyday transactions. By posing this new unsolved challenge to the power and promise of Artificial Intelligence (AI), this work leads the way towards closing that chasm by real-time recognition and translation of full ASL. Our approach employs a novel variant of Random Forest and utilizes cutting-edge video processing techniques to identify and understand the nuanced, often exquisitely delicate detail of ASL signing, at unprecedented levels of accuracy, and at speed. Another layer of innovation that characterizes our work is our integration of augmented reality (AR). By embedding AR along with our translator of artificial intelligence tech, we intend to completely change the way American Sign Language (ASL) is conveyed by directly engraining our already robust Random Forest model and advanced video processing techniques to project the ASL translation directly into your visual field in real time. The goal to demystify this complex and vivid language and, in doing so, to remove the communication barriers that persist between the Deaf community and the rest of the world, thus, fostering inclusion. © 2024 IEEE.

关键词： Augmented reality

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