Design and Optimization of an FPGA-Based Infrared Dim Small Target Detection Network Under a Sky Cloud Background by Yongbo Cheng, Xuefeng Lai, Yucheng Xia

“…The network enhances detection performance through sequential-differential inputs, false-alarm-object learning, and multi-anchor assignment while reducing computational overhead through sequential-differential acceleration and convolutional pooling. Deployment efficiency is improved via image channel optimization, mixed quantization, and refining the infrared image calibration set. …”
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Fast jet tagging with MLP-Mixers on FPGAs by Chang Sun, Jennifer Ngadiuba, Maurizio Pierini, Maria Spiropulu

“…By using advanced optimization techniques such as High-Granularity Quantization and Distributed Arithmetic, we achieve unprecedented efficiency. …”
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TANS: A Tolerance-Aware Neighborhood Search Method for Workflow Scheduling with Uncertainties in Cloud Manufacturing by Haiyan Xu, Fanhao Ma, Long Chen

“…Workflow tasks in cloud manufacturing often involve uncertain execution and logistics times due to large-scale and geographically distributed resources, creating significant challenges for efficient and reliable scheduling. To address these challenges, we propose the Tolerance-aware Neighborhood Search (TANS) algorithm, which integrates fuzzy time quantization with heuristic neighborhood search techniques. …”
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Dual-Branch Neural Network-Based In-Loop Filter for VVC Intra Coding Using Spatial-Frequency Feature Fusion by Zhen Feng, Xu Liu, Cheolkon Jung

“…In company with the reconstructed frame, the quantization parameter (QP) map, the predicted frame, and the partition frame are popularly used as auxiliary input for the neural network-based in-loop filter (NNLF). …”
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Optimized AI and IoT-Driven Framework for Intelligent Water Resource Management by Mahmoud Badee Rokaya Mahmoud, Dalia Ismaeil Ibrahim Hemdan, Samah Hazzaa Alajmani, Raneem Yousif Alyami, Ghada Elmarhomy, Hassan Hashim, El-Sayed Atlam

“…Moreover, ontology-based feature structuring enhances interpretability, while hyperparameter tuning (GridSearchCV, Bayesian Optimization) and model compression techniques (pruning, quantization, knowledge distillation) ensure computational efficiency. …”
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Research on YOLOv3 model compression strategy for UAV deployment by Fei Xu, Litao Huang, Xiaoyang Gao, Tingting Yu, Leyi Zhang

“…Finally, since the training data is a 32-bit floating point number, DoReFa-Net quantization method is used to quantify the model, so as to compress the storage capacity of the model. …”
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Lightweight deep learning for real-time road distress detection on mobile devices by Yuanyuan Hu, Ning Chen, Yue Hou, Xingshi Lin, Baohong Jing, Pengfei Liu

“…Utilizing a diverse dataset collected from Europe and Asia, MobiLiteNet incorporates Efficient Channel Attention to boost model performance, followed by structural refinement, sparse knowledge distillation, structured pruning, and quantization to significantly increase the computational efficiency while preserving high detection accuracy. …”
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Robust DOA Estimation via a Deep Learning Framework with Joint Spatial–Temporal Information Fusion by Yonghong Zhao, Xiumei Fan, Jisong Liu

“…In addition, it offers distinct advantages in terms of generalization and computational efficiency.…”
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A Configurable Accelerator for CNN-Based Remote Sensing Object Detection on FPGAs by Yingzhao Shao, Jincheng Shang, Yunsong Li, Yueli Ding, Mingming Zhang, Ke Ren, Yang Liu

“…This paper proposes a new generation of high flexibility and intelligent CNNs hardware accelerator for satellite remote sensing in order to make its computing carrier more lightweight and efficient. A data quantization scheme for INT16 or INT8 is designed based on the idea of dynamic fixed point numbers and is applied to different scenarios. …”
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An innovative traffic flow detection model based on temporal video frame analysis and grayscale aggregation quantification by Xin Liu, Qiao Meng, Xin Li, Zhijie Wang, Siyuan Kong, Bingyu Li

“…Additionally, the model improves computing resource efficiency by approximately 72.5% and demonstrates substantial real‐time detection capabilities.…”
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Hybrid CNN–BiLSTM–DNN Approach for Detecting Cybersecurity Threats in IoT Networks by Bright Agbor Agbor, Bliss Utibe-Abasi Stephen, Philip Asuquo, Uduak Onofiok Luke, Victor Anaga

“…Advanced optimization techniques, including model pruning and quantization, are applied to enhance deployment efficiency in resource-constrained IoT environments. …”
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Visual Positioning Detection of EMU Brake Pad Based on Deep Learning by GUAN Chunling, XU Yingjie, SONG Yuechao

“…To address the issues of low efficiency, missed and false detections in the manual inspection of EMU (electric multiple unit) brake pads, it is necessary to study visual positioning detection methods for EMU brake pads. …”
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RDM-YOLO: A Lightweight Multi-Scale Model for Real-Time Behavior Recognition of Fourth Instar Silkworms in Sericulture by Jinye Gao, Jun Sun, Xiaohong Wu, Chunxia Dai

“…Second, standard convolutional layers are replaced with distribution shifting convolution (DSConv), leveraging dynamic sparsity and quantization mechanisms to reduce computational complexity. …”
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Proactive Scheduling and Routing of MRP-Based Production with Constrained Resources by Jarosław Wikarek, Paweł Sitek

“…., tools, workers), technological breaks, and time quantization. Key results include determining order feasibility, identifying unfulfilled order components, minimizing costs, shortening deadlines, and assessing feasibility in the absence of available resources. …”
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A novel method for power transformer fault diagnosis considering imbalanced data samples by Jun Chen, Yong Wang, Lingming Kong, Yilong Chen, Mianzhi Chen, Qian Cai, Gehao Sheng

“…We derive a sample parameter correlation quantization matrix from oil chromatography fault data using association rules, which serves as the initial value for the NCA algorithm’s training metric matrix. …”
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Retracted: Computer Medical Image Segmentation Based on Neural Network by Xiaopeng Wang, Lei Gu, Zhongyi Wang

“…This method introduces a non-linear template and data quantization on the basis of a basic network model, which greatly reduces the computational complexity while maintaining the accuracy of image segmentation. …”
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Adaptive Lossy Color Image Compression System Based on Hybrid Algorithm by Husam Khalid Khammas, Ayça Kurnaz Türkben

“…To implement this proposed method three experiments were performed by using images of varying dimensions, namely (256 * 256), (512 * 512), and (1024 * 1024) and four different quantization coefficients. For efficiency performance measurement of the proposed system, three metrics were used: Peak signal-to-noise ratio (PSNR), Structural similarity index (SSIM), and compression ratio (CR). …”
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Incremental learning with SVM for multimodal classification of prostatic adenocarcinoma. by José Fernando García Molina, Lei Zheng, Metin Sertdemir, Dietmar J Dinter, Stefan Schönberg, Matthias Rädle

“…First- and second-order angular independent statistical approaches and rotation invariant local phase quantization (RI-LPQ) were utilized to quantify texture information. …”
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On-Chip Photonic Convolutional Processing Lights Up Fourier Neural Operator by Zilong Tao, Hao Ouyang, Qiuquan Yan, Shiyin Du, Hao Hao, Jun Zhang, Jie You

“…Fourier Neural Operators (FNOs) have gained increasing attention for their effectiveness in extracting frequencydomain features and efficiently approximating functions, making them wellsuited for classification tasks. …”
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Microcontroller-Based EdgeML: Health Monitoring for Stress and Sleep via HRV by Priyanshu Srivastava, Namita Shah, Kavita Jaiswal

“…However, traditional ML systems often face challenges in real-time processing and resource efficiency, limiting their application in life-critical scenarios. …”
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