Intelligent energy saving measurement method and realization of power grid based on IoT by Dapin ZHANG, Qinghai OU, Yeshen HE, Yiying ZHANG

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Application of Object Contrast for Forming Images Used in Technical Vision Systems for Navigation of Mobile Robots by Tymochko O., Boichenko О., Zakirov S., Holovniak D., Dmitriiev O., Padalka I.

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SpiNeRF: direct-trained spiking neural networks for efficient neural radiance field rendering by Xingting Yao, Xingting Yao, Qinghao Hu, Fei Zhou, Tielong Liu, Tielong Liu, Zitao Mo, Zeyu Zhu, Zeyu Zhu, Zhengyang Zhuge, Jian Cheng, Jian Cheng

“…Experiments on multiple datasets demonstrate that our method outperforms previous SNN encoding schemes and artificial neural network (ANN) quantization methods in both rendering quality and energy efficiency. …”
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Neural architecture codesign for fast physics applications by Jason Weitz, Dmitri Demler, Luke McDermott, Nhan Tran, Javier Duarte

“…We exceed performance on various tasks and show further speedup through model compression techniques such as quantization-aware-training and neural network pruning. …”
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Comparative analysis of model compression techniques for achieving carbon efficient AI by Eileen Paula, Jayesh Soni, Himanshu Upadhyay, Leonel Lagos

“…We also compared the energy efficiency of these compressed models against inherently carbon-efficient transformer models, such as TinyBERT and MobileBERT. …”
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Cooperative Detection for Cell-Free Massive MIMO With Multiple Central Processing Units Under Backhaul Capacity Limitation by Faurdoir Ndimumahoro, Koji Ishibashi

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Filter Implementation for Power-Efficient Chromatic Dispersion Compensation by Christoffer Fougstedt, Alireza Sheikh, Pontus Johannisson, Per Larsson-Edefors

“…Chromatic dispersion (CD) compensation in coherent fiber-optic systems represents a very significant DSP block in terms of power dissipation. Since spectrally efficient coherent systems are expected to find a wider deployment in systems shorter than long haul, it becomes relevant to investigate filter implementation aspects of CD compensation in the context of systems with low-to-moderate amounts of accumulated dispersion. …”
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An Intelligent Smart Dynamic Feature Analysis Based Approach by Utilizing Deep Learning to Improve the Breast Cancer Detection by Seong-O Shim, Lal Hussain, Eesa Alsolami, Monagi H. Alkinani

“…The model was also trained using Quantization aware training (QAT) to enable efficient deployment on low-resource devices without significant performance degradation. …”
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A survey of model compression techniques: past, present, and future by Defu Liu, Yixiao Zhu, Zhe Liu, Yi Liu, Changlin Han, Jinkai Tian, Ruihao Li, Wei Yi

“…To meet the urgent demand for efficient deployment, we delve into several compression methods—such as quantization, pruning, low-rank decomposition, and knowledge distillation—emphasizing their fundamental principles, recent advancements, and innovative strategies. …”
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Optimized Ensemble Deep Learning for Real-Time Intrusion Detection on Resource-Constrained Raspberry Pi Devices by Muhammad Bisri Musthafa, Samsul Huda, Tuy Tan Nguyen, Yuta Kodera, Yasuyuki Nogami

“…The proposed system maintains high detection performance with accuracy of 97.3% across all test scenarios, while efficiently leveraging multi-core processing with peak CPU usage reaching 111.8%. …”
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An SLA-based resource scheduling method in hybrid cloud environment by UXiaofeng XU, Jinsong XU

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Effective thermal conductivity and inner transfer surface of porous and fibrous materials on the example of foodstuffs by Yu. V. Svetlov, Yu. B. Nikiforov

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Collaborative Learning for Task-Oriented Semantic Communications: Overcoming Data Mismatch Between Transceivers by Yanhu Wang, Ruidong Li, Changhong Wang, Jia Ye, Chenyuan Feng, Shuaishuai Guo

“…Task-oriented semantic communication (ToSC) enhances efficiency and performance by leveraging task-specific data representations and end-to-end learning, which are more compact and effective than traditional reconstruction-oriented methods. …”
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GMT: Gzip-based Memory-efficient Time-series classification by Sungmin Lee, Kichang Lee, JaeYeon Park, JeongGil Ko

“…We introduce GMT, a memory-efficient parameter-free classifier that uses gzip compressor and k-nearest neighbors (kNN) for classifying multi-channel time-series data. …”
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An Efficient Architecture for Edge AI Federated Learning With Homomorphic Encryption by Dadmehr Rahbari, Masoud Daneshtalab, Maksim Jenihhin

“…With the rapid growth of edge AI applications, there is an increasing demand for federated learning (FL) frameworks that are both efficient and privacy-preserving. This work introduces a robust approach that leverages homomorphic encryption (HE) to ensure data confidentiality during decentralized training. …”
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Energy-Efficient Deep Learning for Cloud Detection Onboard Nanosatellite by Imane Khalil, Amina Daghouri, Mohammed Alae Chanoui, Zouhair Guennoun, Adnane Addaim

“…The customized SegNet architecture, tailored with minimal kernels and layers, achieved an accuracy of 93.50%, effectively balancing performance and computational efficiency. Quantization further optimized energy consumption, achieving a reduction of 82.2% at 280 MHz. …”
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Efficient Real-Time Isotope Identification on SoC FPGA by Katherine Guerrero-Morejón, José María Hinojo-Montero, Jorge Jiménez-Sánchez, Cristian Rocha-Jácome, Ramón González-Carvajal, Fernando Muñoz-Chavero

“…Efficient real-time isotope identification is a critical challenge in nuclear spectroscopy, with important applications such as radiation monitoring, nuclear waste management, and medical imaging. …”
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Design and Implementation of a Lightweight and Energy-Efficient Semantic Segmentation Accelerator for Embedded Platforms by Hui Li, Jinyi Li, Bowen Li, Zhengqian Miao, Shengli Lu

“…However, realizing efficient semantic segmentation on resource-constrained embedded platforms still faces many challenges. …”
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Deep Learning Model Compression and Hardware Acceleration for High-Performance Foreign Material Detection on Poultry Meat Using NIR Hyperspectral Imaging by Zirak Khan, Seung-Chul Yoon, Suchendra M. Bhandarkar

“…Ensuring the safety and quality of poultry products requires efficient detection and removal of foreign materials during processing. …”
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An all integer-based spiking neural network with dynamic threshold adaptation by Chenglong Zou, Chenglong Zou, Xiaoxin Cui, Shuo Feng, Guang Chen, Yi Zhong, Zhenhui Dai, Yuan Wang

“…Due to this all integer-based quantization process, the required computational operations are significantly reduced, potentially providing a substantial energy efficiency advantage for numerous edge computing applications.…”
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