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EPDTNet + -EM: Advanced Transfer Learning and SubNet Architecture for Medical Image Diagnosis

Cognitive Computation 2025年第2期17卷 1-22页

作者： K, Dhivya K, Sangamithrai S, Indra Priyadharshini M, Vedaraj Department of Electronics and Communication Engineering SRM Institute of Science and Technology Tamilnadu Kattankulathur India Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R & d Institute of Science and Technology Tamilnadu Chennai India School of Computer Science and Engineering Vellore Institute of Technology Chennai India Department of Computer Science and Engineering R.M.D. Engineering College RSM Nagar Tamilnadu Kavaraipettai Thiruvallur601206 India

This paper presents a novel medical imaging framework, Efficient Parallel Deep Transfer SubNet+-based Explainable Model (EPDTNet + -EM), designed to improve the detection and classification of abnormalities in medical images. The model integrates Enhanced Exponential Transfer Learning (En-ETL) and the Parallel SubNet (PSNet +) architecture, addressing challenges like overfitting, high computational cost, and limited generalization across complex datasets. En-ETL accelerates learning and enhances precision, while PSNet + balances computational efficiency and performance through parallel convolutional layers and an axis attention mechanism. The proposed framework preprocesses medical images using resizing, noise removal, and contrast enhancement, ensuring high-quality inputs for analysis. For classification, the PSNet + model categorizes medical images into normal and abnormal cases. Explainable AI (XAI) is applied to highlight key features in classified images, improving interpretability and clinical decision-making. Experimental results validate the framework on various datasets, including MRI, CT, X-ray, and mammography images. The proposed model achieves a classification accuracy of 98.83%, a false positive rate of 2%, and an execution time of 5.3 ms. Comparative Analysis show superior performance over existing approaches in classification accuracy and efficiency. Ablation studies confirmed the significant contributions of the proposed model using each component in enhancing performance. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Transfer learning

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Modeling and Simulation of Virtual Reality Assistive Tool for Children with Autism Spectral Disorder 2nd

Modeling and Simulation of Virtual Reality Assistive Tool fo...

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2nd International Conference on Deep Sciences for Computing and communications, IconDeepCom 2023

作者： NirmalaPriya, G. Shree Aravindh, S.S. Tharun, D. Deepak, M. Hermalin, Cynthiya S. Department of Electronics and Communication Engineering Rajalakshmi Institute of Technology Chennai India Department of Computer and Communication Engineering Rajalakshmi Institute of Technology Chennai India

ISBN: (纸本)9783031689079

Autism spectrum disorder (ASD) is a prevalent issue contributing to deprivation among people in terms of their capability to maintain social relationships and interact normally with fellow members of society. Teens with ASD battle to exercise proper sociable behavior as well as mingle with others sharing the same age range. It affects all sorts of races, ethnicities and budgets alike. Despite its long- term nature, ASD has therapies and treatments that can help address issues associated with it such as restlessness, aggression, repetitive behavior, focus difficulties, worry and depression through the use of medicine. The use of virtual reality-based training, in addition to medical intervention, may be used to address various behavioral tradeoffs through repeated conditioning and learning. A variety of learning scenarios that would be unsafe, challenging, or time-consuming to set up or frequently recreate in the real world can now be simulated using virtual reality (VR) technology. In this paper, a virtual reality simulator for with the aid of social educators, achieve this goal. This study used the gaming program Social Activity Trainer to simulate and construct a virtual reality (VR)-based assistive aid (SAT). The assistive tool was created to help youngsters with ASD interact and use social skills. Based on three key skills—facial expression recognition, reading comprehension, and task delivery—seven tasks were created for the VR assistive tool. There are seven modules in a virtual reality scenario, including one for music therapy. The EEG signals are looked at to assess the degree of autism in 10 ASD children who participated in the test. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Diseases

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A survey on semantic communications:Technologies,solutions,applications and challenges

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Digital communications and Networks 2024年第3期10卷 528-545页

作者： Yating Liu Xiaojie Wang Zhaolong Ning MengChu Zhou Lei Guo Behrouz Jedari School of Communication and Information Engineering Chongqing University of Posts and TelecommunicationsChongqing 400065China Baotou Vocational&Technical College Baotou 014035China School of Information and Electronic Engineering Zhejiang Gongshang UniversityHangzhou 310018China Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102USA Nokia Finland

Semantic communication(SC)has emerged as a novel communication paradigm that provides a receiver with meaningful information extracted from the source to maximize information transmission throughput in wireless networks,beyond the theoretical capacity *** the extensive research on SC,there is a lack of comprehensive survey on technologies,solutions,applications,and challenges for *** this article,the development of SC is first reviewed and its characteristics,architecture,and advantages are ***,key technologies such as semantic extraction,semantic encoding,and semantic segmentation are discussed and their corresponding solutions in terms of efficiency,robustness,adaptability,and reliability are *** of SC to UAV communication,remote image sensing and fusion,intelligent transportation,and healthcare are also presented and their strategies are ***,some challenges and future research directions are presented to provide guidance for further research of SC.

关键词： Semantic communication Semantic coding Semantic extraction Semantic communication framework Semantic communication applications

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CS2DIPs: Unsupervised HSI Super-Resolution Using Coupled Spatial and Spectral DIPs

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IEEE Transactions on Image Processing 2024年 33卷 3090-3101页

作者： Fang, Yuan Liu, Yipeng Chi, Chong-Yung Long, Zhen Zhu, Ce University of Electronic Science and Technology of China School of Communication and Information Engineering Chengdu611731 China National Tsing Hua University Institute of Communications Engineering Department of Electrical Engineering Hsinchu30013 Taiwan

In recent years, fusing high spatial resolution multispectral images (HR-MSIs) and low spatial resolution hyperspectral images (LR-HSIs) has become a widely used approach for hyperspectral image super-resolution (HSI-SR). Various unsupervised HSI-SR methods based on deep image prior (DIP) have gained wide popularity thanks to no pre-training requirement. However, DIP-based methods often demonstrate mediocre performance in extracting latent information from the data. To resolve this performance deficiency, we propose a coupled spatial and spectral deep image priors (CS2DIPs) method for the fusion of an HR-MSI and an LR-HSI into an HR-HSI. Specifically, we integrate the nonnegative matrix-vector tensor factorization (NMVTF) into the DIP framework to jointly learn the abundance tensor and spectral feature matrix. The two coupled DIPs are designed to capture essential spatial and spectral features in parallel from the observed HR-MSI and LR-HSI, respectively, which are then used to guide the generation of the abundance tensor and spectral signature matrix for the fusion of the HSI-SR by mode-3 tensor product, meanwhile taking some inherent physical constraints into account. Free from any training data, the proposed CS2DIPs can effectively capture rich spatial and spectral information. As a result, it exhibits much superior performance and convergence speed over most existing DIP-based methods. Extensive experiments are provided to demonstrate its state-of-the-art overall performance including comparison with benchmark peer methods. © 1992-2012 IEEE.

关键词： Tensors

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Optimized Convolutional Neural Network at the IoT edge for image detection using pruning and quantization

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Multimedia Tools and Applications 2025年第9期84卷 5435-5455页

作者： Naveen, Soumyalatha Kounte, Manjunath R Department of Computer Science and Engineering Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Manipal India School of Electronics and Communication Engineering REVA University Bangalore India

Most real-time computer vision applications heavily rely on Convolutional Neural Network (CNN) based models, for image classification and recognition. Due to the computationally and memory-intensive nature of the CNN model, it’s challenging to deploy on resource-constrained Internet of Things (IoT) devices to enable Edge intelligence for real-time decision-making. Edge intelligence requires minimum inference latency, memory footprint, and energy-efficient model. This work aims to develop an energy-efficient deep learning accelerator using a 3-stage pipeline: Training, Weight-pruning, and Quantization to reduce the model size and optimize the resources. First, we employ YOLOv3, a CNN architecture to detect objects in an image on the trained data. In addition, a sparse network of YOLO has been created by using pruning, which helps to improve the network’s performance and efficiency by reducing the computational requirements. Finally, we utilize 8-bit quantization to reduce the precision of the weights and activations, in a neural network. The evaluation of our proposed model shows that combining pruning and 8-bit quantization improves the efficiency and performance of the model. While pruning shows a decline of 80.39% in model parameters. The combination of 8-bit quantization results in an improvement in inference latency by 22.72% compared to existing SQuantization approach and a reduction of energy consumption by 29.41%. © The Author(s) 2024.

关键词： Convolutional neural networks

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Noise Estimation from Degraded Speech

Noise Estimation from Degraded Speech

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International Conference on 6G communications Networking and Signal Processing, SGCNSP 2023

作者： Thorbole, Shubham Raj, Rahul Upadhyay, Navneet Department of Electronics and Communication Engineering The LNM Institute of Information Technology Jaipur India Department of Computer and Communication Engineering The LNM Institute of Information Technology Jaipur India

ISBN: (纸本)9789819778751

In real-world scenarios, speech signals are often corrupted by various types of noise, which can significantly degrade the intelligibility and quality of the speech. Noise in such environments is highly non-stationary, changing rapidly and unpredictably. A new algorithm has been created to estimate noise in speech signals affected by rapidly changing and unpredictable non-stationary noise. This algorithm aims to enhance speech quality and intelligibility in challenging acoustic settings. It determines signal presence by comparing the power spectrum of noisy speech to a continually updated local minimum, calculated from past noisy speech power spectra with a look-ahead factor. Its standout feature is its rapid adaptability to swiftly respond to new noise patterns, crucial for maintaining speech clarity and quality in dynamic noise environments. Formal experiments validated its effectiveness compared to other noise-estimation methods when integrated into speech enhancement systems, using metrics like mean squared error (MSE) and signal to noise ratio (SNR). This algorithm significantly contributes to noise estimation and voice enhancement, offering effectiveness in handling highly non-stationary noise and being adaptable and versatile for various applications. This algorithm stands as a substantial advancement in the domains of noise estimation and voice enhancement overall. Its utility extends across diverse applications owing to its proficiency in handling highly non-stationary noise conditions, coupled with its adaptability and versatility. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Background noise

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A Miniature Hexa-Band Antenna for Internet of Things Applications Using Six Quarter-wavelength Resonators

Advanced Electromagnetics

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Advanced Electromagnetics 2025年第1期14卷 52-58页

作者： Hasan, Yousif Mohsin Rahman, Zain-Aldeen S. A. Al-Yasir, Yasir I. A. Department of Electronic and Communication Engineering College of Engineering University of Al-Qadisiyah Iraq Department of Electrical Techniques Technical Institute/Qurna Southern Technical University Basra61016 Iraq Communication and Space Systems Engineering Research Team Manchester Metropolitan University Manchester United Kingdom Communications Engineering Department Iraq University College Basra Iraq

This work presents a compact, low-cost hexa-band microstrip antenna for Internet of Things (IoT) applications. The proposed hexa-band antenna is composed of simple six-λ/4 resonators to generate six resonant frequencies: GSM 1.84 GHz (1.8-1.89 GHz), Bluetooth 2.31 GHz (2.25 –2.375 GHz), WiMAX 3.3 GHz (3.16-3.47 GHz), WiFi 4.63 GHz (4.34-5 GHz), upper WLAN 6.1 GHz (5.8-6.91 GHz) and X-band 9.26 GHz (8.87-9.83 GHz). The proposed hexa-band antenna is fabricated using FR4 substrate with (23 × 20 × 1.6) mm3 dimensions, and its measured results are presented to validate the simulated results. The results of simulations and measurements are used to examine the radiation properties, including radiation patterns, gain, efficiency, VSWR, and reflection coefficient. The proposed hexa-band antenna has a miniaturized size and good radiation performance. © 2025, Advanced Electromagnetics. All rights reserved.

关键词： Wireless local area networks (WLAN)

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Hardware-friendly rate estimation algorithm and architecture design for AVS3

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Multimedia Tools and Applications 2025年 1-19页

作者： Yan, Yunyao Xiang, Guoqing Chen, Jie Huang, Xiaofeng Zhang, Peng Jia, Huizhu Xie, Xiaodong School of Electronic and Computer Engineering Peking University Shenzhen China School of Computer Science Peking University Beijing China Advanced Institute of Information Technology Peking University Hangzhou China School of Communication Engineering Hangzhou Dianzi University Hangzhou China

To enhance the capabilities of advanced video coding for emerging applications, the AVS3 standard has been introduced to double the coding efficiency compared to its predecessor, the AVS2 standard. It incorporates sophisticated coding tools, such as advanced rate-distortion optimization (RDO), to select the optimal coding mode. The AVS3 standard further refines bit rate compression through Advanced Entropy Coding (AEC) within the RDO process. However, AEC demands significant computational resources due to its high data dependency and involves complex steps like binarization, context modeling, interval subdivision, renormalization, handling of outstanding bits, and context updating. Notably, the time complexity of AEC is predominantly due to context updating and interval subdivision, which are recursive and thus pose challenges for real-time applications, particularly in hardware implementations. Addressing these challenges, this paper introduces an adaptive rate estimation algorithm using a hardware-friendly piece-wise linear function to expedite bit rate calculations for AVS3 applications. Initially, we develop a linear rate estimation method based on the statistics of bin numbers. To preserve high coding performance, we further propose an adaptive model parameter updating method that adjusts weights dynamically based on varying video content. Building on this fast rate estimation algorithm, we propose a high-throughput hardware architecture that incorporates pipelining and parallelization to meet the stringent real-time requirements for 4K@120fps ultra-high-definition video at 200 MHz, with only a minimal increase in BD-rate by 1.06% under the All-Intra (AI) configuration. To our knowledge, this is the pioneering study focusing on hardware-oriented rate estimation for the AVS3 standard, marking a significant advancement in the field of video coding technology. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature

关键词： Video signal processing

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Mobility Stick with Haptic Feedback for People with Vision Impairments

Mobility Stick with Haptic Feedback for People with Vision I...

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2024 International Conference on Signal Processing, Computation, electronics, Power and Telecommunication, IConSCEPT 2024

作者： Raghul, J. Durga Devi, K. Sreya, M. Maithreye, S. SRM Institute of Science and Technology Department of Electronic and Computer Engineering Chennai Ramapuram India SRM Institute of Science and Technology Department of Electronics and Communication Engineering Chennai Ramapuram India

ISBN: (纸本)9798331540685

In this research, haptic motor, Node MCU, ultrasonic sensors are used to address the problem associated with the current walking stick for visually disabled people. These problems include disturbing their main sense of survival which is hearing. Hence, a system containing ultrasonic sensors, haptic motor and Internet of Things has been recommended in this study. This study illustrates that the implementation of haptic motors and ultrasonic sensors can successfully address the major issues that current alternatives face and it has a positive ad significant impact on visually disabled people. Using this method, one can monitor the person's movement and whether they fell down. This system makes use of IoT it integrate the data from sensors and update it onto the website for other person monitoring. © 2024 IEEE.

关键词： Ultrasonic sensors

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4D-printed intelligent reflecting surface with improved beam resolution via both phase modulation and space modulation

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Microsystems & Nanoengineering 2024年第5期10卷 407-415页

作者： Kyounghwan Kim Ratanak Phon Eiyong Park Sungjoon Lim Department of Intelligent Semiconductor Engineering Chung-Ang UniversitySeoul 06974Republic of Korea Department of Electrical and Computer Engineering Stevens Institute of TechnologyHoboken NJ 07030USA School of Electrical and Electronic Engineering Chung-Ang UniversitySeoul 06974Republic of Korea

Recently,intelligent reflecting surfaces(IRSs)have emerged as potential candidates for overcoming the line-of-sight issue in 5 G/6 G wireless *** IRSs can manipulate the direction of reflected beams,enabling efficient beam steering to enhance the performance of wireless *** unit cell(or unit structure)of an IRS commonly consists of electrical elements for phase ***,by employing phase modulation alone,an IRS can steer the reflected electromagnetic waves toward only discrete and specific angles,leaving a wide range of out-of-beam *** this work,an IRS that uses both phase modulation and space modulation is presented to improve the beam resolution and continuously cover out-of-beam areas that phase modulation alone cannot address.A positive-intrinsic-negative diode is mounted on a unit cell for phase modulation,and a 4D-printed reconfigured structure is fabricated to demonstrate space *** beam-steering function is achieved by alternating the states of the diodes in the same columns,while the beam resolution is improved by controlling the gaps between the *** functions are frst theoretically and numerically analyzed and then experimentally verified,demonstrating that additional angles of-46°/+50°,-22°/+14°,and -16°/+12°are achieved with space modulation and -60°/+62°,-30°/+22°,and±16°are achieved by phase modulation *** proposed IRS offers the possibility of functional integration in a variety of indoor applications within the wireless communication field.

关键词： alone beam columns

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