Reducing Memory and Computational Cost for Deep Neural Network Training with Quantized Parameter Updates by Leo Buron, Andreas Erbslöh, Gregor Schiele

“…For embedded devices, both memory and computational efficiency are essential due to their constrained resources. …”
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Strategies for enhancing deep video encoding efficiency using the Convolutional Neural Network in a hyperautomation mechanism by Xiaolan Wang

“…This study focuses on deep video encoding and proposes an efficient encoding method that integrates the Convolutional Neural Network (CNN) with a hyperautomation mechanism. …”
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YOLORM: An Advanced Key Point Detection Method for Accurate and Efficient Rotameter Reading in Low Flow Environments by Huang Yong, Xia Xing, Xiao Shengwang

“…Automatic reading of rotameters in low flow and challenging environments poses substantial accuracy and efficiency challenges. To address these issues, this study introduces YOLORM, an advanced key point detection method for rotameters, built upon the YOLOv8n model. …”
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Resource-Efficient Cotton Network: A Lightweight Deep Learning Framework for Cotton Disease and Pest Classification by Zhengle Wang, Heng-Wei Zhang, Ying-Qiang Dai, Kangning Cui, Haihua Wang, Peng W. Chee, Rui-Feng Wang

“…Built upon the MobileViTv2 backbone, RF-Cott-Net integrates an early exit mechanism and quantization-aware training (QAT) to enhance deployment efficiency without sacrificing accuracy. …”
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An SLA-based resource scheduling method in hybrid cloud environment by UXiaofeng XU, Jinsong XU

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Enhanced Vector Quantization for Embedded Machine Learning: A Post-Training Approach With Incremental Clustering by Thommas K. S. Flores, Morsinaldo Medeiros, Marianne Silva, Daniel G. Costa, Ivanovitch Silva

“…TinyML enables the deployment of Machine Learning (ML) models on resource-constrained devices, addressing a growing need for efficient, low-power AI solutions. However, significant challenges remain due to strict memory, processing, and energy limitations. …”
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Efficient hardware implementation of interpretable machine learning based on deep neural network representations for sensor data processing by J. Schauer, P. Goodarzi, A. Schütze, T. Schneider

“…This representation retains the interpretability but allows efficient implementation on hardware to process the acquired data directly on the sensor node. …”
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KronNet a lightweight Kronecker enhanced feed forward neural network for efficient IoT intrusion detection by Saeed Ullah, Junsheng Wu, Mian Muhammad Kamal, Abdul Khader Jilani Saudagar

“…Abstract The rapid expansion of Internet of Things (IoT) networks necessitates efficient intrusion detection systems (IDS) capable of operating within the stringent resource constraints of IoT devices. …”
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FPGA Acceleration With Hessian-Based Comprehensive Intra-Layer Mixed-Precision Quantization for Transformer Models by Woohong Byun, Jongseok Woo, Saibal Mukhopadhyay

“…Our concurrent quantization method balances the benefits of row-wise weight quantization and Query-Key coupled activation quantization while maximizing energy efficiency through multi-precision optimization. …”
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Knowledge- and Model-Driven Deep Reinforcement Learning for Efficient Federated Edge Learning: Single- and Multi-Agent Frameworks by Yangchen Li, Lingzhi Zhao, Tianle Wang, Lianghui Ding, Feng Yang

“…In this paper, we investigate federated learning (FL) efficiency improvement in practical edge computing systems, where edge workers have non-independent and identically distributed (non-IID) local data, as well as dynamic and heterogeneous computing and communication capabilities. …”
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GENERATING OF OPTIMAL QUANTIZATION LEVELS OF CONTROL CURRENTS FOR LINEAR STEPPING DRIVES OF PRECISION MOTION SYSTEMS by I. V. Dainiak, V. P. Oger, D. S. Tsitko, D. G. Begun

“…The investigations have proved an efficiency of the proposed algorithm and methodology for forming coordinate discrete grid.…”
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Generation of Phase-Only Fourier Hologram Based on Double Phase Method and Quantization Error Analysis by Yang Wu, Jun Wang, Chun Chen, Chan-Juan Liu, Feng-Ming Jin, Yu-Hen Hu

“…The double phase method is an efficient way to generate phase-only holograms with high reconstruction quality due to no addition of a random phase. …”
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Optimising TinyML with quantization and distillation of transformer and mamba models for indoor localisation on edge devices by Thanaphon Suwannaphong, Ferdian Jovan, Ian Craddock, Ryan McConville

“…Abstract This paper proposes small and efficient machine learning models (TinyML) for resource-constrained edge devices, specifically for on-device indoor localisation. …”
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QDLTrans: Enhancing English Neural Machine Translation With Quantized Attention Block and Tunable Dual Learning by Xing Liu

“…Specifically, our method outperforms existing approaches in both translation quality and efficiency, offering a balanced solution for enhancing NMT in low-resource settings.…”
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Enabling Flexible Link Capacity for eCPRI-Based Fronthaul With Load-Adaptive Quantization Resolution by Longsheng Li, Meihua Bi, Haiyun Xin, Yunhao Zhang, Yan Fu, Xin Miao, Ahmed Mohanmmed Mikaeil, Weisheng Hu

“…Bandwidth-efficient 5G optical fronthaul interfaces, such as the Ethernet-based common public radio interface (eCPRI), with novel low layer split (LLS) are being actively investigated. …”
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Sliding Mode Control of Uncertain Switched Systems via Length-Limited Coding Dynamic Quantization by Qinqi Xu, Haijuan Zhao

“…To address these issues, a dynamic quantizer is introduced to efficiently encode the system state while minimizing quantization error under the constraint of the finite code length. …”
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Energy-efficient deep learning-based intrusion detection system for edge computing: a novel DNN-KDQ model by Hafiz Gulfam Ahmad Umar, Iqra Yasmeen, Muhammad Aoun, Tehseen Mazhar, Muhammad Amir Khan, Ines Hilali Jaghdam, Habib Hamam

“…This research proposes an energy-efficient IDS framework based on a modified Deep Neural Network with Knowledge Distillation and Quantization (DNN-KDQ) to address these challenges. …”
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Deep combining of local phase quantization and histogram of oriented gradients for indoor positioning based on smartphone camera by Jichao Jiao, Zhongliang Deng

“…The experimental results show that accurate and efficient indoor location positioning is achieved.…”
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NeuroDetect: Deep Learning-Based Signal Detection in Phase-Modulated Systems with Low-Resolution Quantization by Chanula Luckshan, Samiru Gayan, Hazer Inaltekin, Ruhui Zhang, David Akman

“…We rigorously investigate the interplay between ADC resolution and detection accuracy, introducing novel penalty metrics that quantify the effects of both quantization and learning errors. Our results shed light on the design trade-offs between ADC resolution and detection accuracy, providing future directions for developing energy-efficient high-speed and wideband wireless systems.…”
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Fuzzy Course Tracking Control of Unmanned Surface Vehicle with Actuator Input Quantization and Event-Triggered Mechanism by Qifu Wang, Chenchen Jiang, Jun Ning, Liying Hao, Yong Yin

“…Finally, simulation tests are used to show the algorithm’s efficiency and usefulness.…”
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