Deep learning system for the auxiliary diagnosis of thyroid eye disease: evaluation of ocular inflammation, eyelid retraction, and eye movement disorder by Yu Han, Jun Xie, Xiaoyu Li, Xinying Xu, Bin Sun, Han Liu, Chunfang Yan

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Two-dimensional materials based two-transistor-two-resistor synaptic kernel for efficient neuromorphic computing by Qian He, Hailiang Wang, Yishu Zhang, Anzhe Chen, Yu Fu, Guodong Xue, Kaihui Liu, Shiman Huang, Yang Xu, Bin Yu

“…Additionally, we introduce the Gaussian noise quantization weight-training scheme alongside the ConvMixer convolution architecture to achieve image dataset identification with high accuracy. …”
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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

“…The proposed YOLORM model has the potential to significantly enhance safety and efficiency in industrial production processes.…”
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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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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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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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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

“…Numerical results demonstrate the effectiveness and advantages of the proposed frameworks in enhancing FL efficiency.…”
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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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Enhanced epilepsy detection using discrete wavelet transform and bandpass filtering on EEG data: integration of ART-based and LVQ models by Seyed Matin Malakouti

“…We evaluate multiple adaptive classifiers, including Adaptive Resonance Theory (ART1, ARTMAP) and Learning Vector Quantization (LVQ), enhanced through grid search and ensemble learning.Experiments were conducted using the Bonn EEG dataset, focusing on classifying interictal and ictal EEG signals. …”
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A novel two-dimensional reversible data hiding scheme based on high-efficiency histogram shifting for JPEG images by Ben He, Yi Chen, Yonghui Zhou, Yongrong Wang, Yanli Chen

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Spectrum-efficient user grouping and resource allocation based on deep reinforcement learning for mmWave massive MIMO-NOMA systems by Minghao Wang, Xin Liu, Fang Wang, Yang Liu, Tianshuang Qiu, Minglu Jin

“…This study proposes a spectrum-efficient and fast convergence deep reinforcement learning (DRL)-based resource allocation framework to optimize user grouping and allocation of subchannel and power. …”
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Quantum-Inspired Multi-Scale Object Detection in UAV Imagery: Advancing Ultra-Small Object Accuracy and Efficiency for Real-Time Applications by Muhammad Muzammul, Muhammad Assam, Ayman Qahmash

“…Efficiency optimizations, including structured pruning and quantization, reduced computational load to 30 GFLOPS with an inference time of 8.1 milliseconds, ensuring suitability for real-time UAV applications on resource-constrained platforms. …”
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Highly Efficient Digitized Quasi-3D Photolithography Based on a Modified Golomb Coding via DMD Laser Direct Writing by Hui Wang, Zhe Huang, Yanting Shen, Shangying Zhou

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Automated deep-learning model optimization framework for microcontrollers by Seungtae Hong, Gunju Park, Jeong-Si Kim

“…We focus on model optimization techniques, particularly pruning and quantization, to enhance the performance of neural networks within the lim-ited resources of MCUs. …”
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Resource Allocation for Federated Learning With Highly Distorted Model by Ryu Junewoo, Nguyen Xuan Tung, Minh-Duong Nguyen, Quang-Vinh do, Won-Joo Hwang

“…Therefore, existing communication-effective federated learning (FL) approaches (e.g., model quantization, data sparsification, and model compression) incurred a considerable trade-off between communication efficiency and global convergence rate when an extreme encryption rate is applied. …”
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Energy-Aware Machine Learning Models—A Review of Recent Techniques and Perspectives by Rafał Różycki, Dorota Agnieszka Solarska, Grzegorz Waligóra

“…Key techniques, such as model compression, pruning, quantization, and cutting-edge hardware design, take center stage in the discussion. …”
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Acceleration of Urdu Optical Character Recognition on Zynq UltraScale+ MPSoC Using Deep Convolutional Neural Network by Fauzia Yasir, Majida Kazmi

“…Benchmarking against CPU and GPU platforms confirmed substantial improvements in speed and energy efficiency. This work establishes a high-performance, scalable, and energy-efficient FPGA-based OCR framework for Urdu and sets the foundation for extending such solutions to other cursive, low-resource languages like Arabic, Pashto, and Persian.…”
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An SLA-based resource scheduling method in hybrid cloud environment by UXiaofeng XU, Jinsong XU

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