High-Performance and Lightweight AI Model with Integrated Self-Attention Layers for Soybean Pod Number Estimation by Qian Huang

“…<b>Methods:</b> To address these challenges, this study presents a set of lightweight, efficient AI models designed to overcome these limitations. …”
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A Digital Simulation Model of Broadband Phased Array RF System and Its Application by Jia Ding, Huaizong Shao, Jianxing Lv, Fake Ding

“…The model research and integrated simulation software construction of the broadband phased array RF system provide an efficient and accurate simulation tool for system design and optimization.…”
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QP-Adaptive Dual-Path Residual Integrated Frequency Transformer for Data-Driven In-Loop Filter in VVC by Cheng-Hsuan Yeh, Chi-Ting Ni, Kuan-Yu Huang, Zheng-Wei Wu, Cheng-Pin Peng, Pei-Yin Chen

“…As AI-enabled embedded systems such as smart TVs and edge devices demand efficient video processing, Versatile Video Coding (VVC/H.266) becomes essential for bandwidth-constrained Multimedia Internet of Things (M-IoT) applications. …”
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Research progress in globular fruit picking recognition algorithm based on deep learning by LI Hui, ZHANG Jun, YU Shuochen, LI Zhixin

“…In the training and deployment phase of the algorithm, the first-stage object detection algorithm uses pruning and quantization techniques to reduce the model size, which is suitable for running in mobile devices or embedded systems with limited resources. …”
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A Channel-Adaptive Range-Doppler Domain Filtering Serial BAQ Algorithm and Comparative Analysis by Tao Jiang, Fubo Zhang, Yi Xie, Chengwei Zhang, Longyong Chen, Yihao Xu, Haibo Tang

“…To address these issues, this paper introduces the Channel-Adaptive Range-Doppler domain filtering Serial Block Adaptive Quantization algorithm (CARDS-BAQ). By incorporating a point-frequency RD domain filtering approach and leveraging serial data matrix splicing and rollback combined with point-frequency ABAQ, CARDS-BAQ enables efficient data compression for arbitrary channel counts. …”
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Scalable FPGA Implementation of a Reliability-Based Direct Turbo Decoder for Short Block Codes by Senthil Murugan, Ramesh Bhakthavatchalu, Karthi Balasubramanian, B. Yamuna, Deepak Mishra, Sree Ranjani Rajendran

“…Additionally, a fixed-point quantization study confirms that a 16-bit representation of reliability values introduces negligible error, offering further scope for area and power optimization. …”
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Silver-based plasmonic nanoparticles for biosensor organophosphate pesticides using a single film containing acetylcholinesterase/choline oxidase by D. Hermanto, N. Ismillayli, H. Muliasari, R. Wirawan, S.R. Kamali

“…BACKGROUND AND OBJECTIVES: To address the potential harm caused by the intensive use of pesticides in pest control in agriculture, there is a need for accurate and efficient methods to detect and monitor pesticide residues. …”
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Real-time fire and smoke detection system for diverse indoor and outdoor industrial environmental conditions using a vision-based transfer learning approach by Uttam U. Deshpande, Goh Kah Ong Michael, Sufola Das Chagas Silva Araujo, Sowmyashree H. Srinivasaiah, Harshel Malawade, Yash Kulkarni, Yash Desai

“…To enable deployment on edge devices, the baseline FP32 model is fine-tuned, pruned, and subsequently optimized using Quantization-Aware Training (QAT) to generate an INT8 precision inference model with its size reduced by 12.7%. …”
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DeepBiteNet: A Lightweight Ensemble Framework for Multiclass Bug Bite Classification Using Image-Based Deep Learning by Doston Khasanov, Halimjon Khujamatov, Muksimova Shakhnoza, Mirjamol Abdullaev, Temur Toshtemirov, Shahzoda Anarova, Cheolwon Lee, Heung-Seok Jeon

“…Our model, optimized for mobile deployment with quantization and TensorFlow Lite, enables rapid on-client computation and eliminates reliance on cloud-based processing. …”
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YOLO-RWY: A Novel Runway Detection Model for Vision-Based Autonomous Landing of Fixed-Wing Unmanned Aerial Vehicles by Ye Li, Yu Xia, Guangji Zheng, Xiaoyang Guo, Qingfeng Li

“…Third, the neck structure is reorganized as a bidirectional feature pyramid network (BiFPN) module with skip connections and attention allocation, enabling efficient multi-scale and across-stage feature fusion. …”
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An open dataset and machine learning algorithms for Niacin Skin-Flushing Response based screening of psychiatric disorders by Xuening Lyu, Rimsa Goperma, Dandan Wang, Chunling Wan, Liang Zhao

“…The core of our methodology involves a novel algorithm featuring an Efficient-Unet based Deep Learning model for the precise segmentation of NSR areas. …”
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Leveraging Large Language Models for Departmental Classification of Medical Records by Baha Ihnaini, Xintong Zeng, Handi Yan, Feige Fang, Abdur Rashid Sangi

“…The models utilize medical records as a dataset for fine-tuning and use clinical knowledge bases to enhance accuracy and efficiency in identifying appropriate departments. This study explores the integration of advanced large language models (LLMs) with quantized low-rank adaptation (QLoRA) for efficient training. …”
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Relationship Study on Land Use Spatial Distribution Structure and Energy-Related Carbon Emission Intensity in Different Land Use Types of Guangdong, China, 1996–2008 by Yi Huang, Bin Xia, Lei Yang

“…The results also indicate that land use spatial distribution structure affects carbon emission intensity more intensively than energy efficiency and production efficiency do. These conclusions provide valuable reference to develop comprehensive policies for energy conservation and carbon emission reduction in a new perspective.…”
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An Optimised CNN Hardware Accelerator Applicable to IoT End Nodes for Disruptive Healthcare by Arfan Ghani, Akinyemi Aina, Chan Hwang See

“…Addressing the challenges posed by constrained dataset sizes, compute-intensive AI algorithms, and hardware limitations, the approach presented in this paper leverages efficient image augmentation and pre-processing techniques to enhance both prediction accuracy and the training efficiency. …”
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Artificial Intelligence on the Identification of Beiguan Music by Yu-Hsin CHANG, Shu-Nung YAO

“…The advantages of this method include improving data processing efficiency, fast MIR, and evoking possible musical connections from the high-relation result of statistical analyses.…”
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GA-VAE: Enhancing Local Feature Representation in VQ-VAE Through Genetic Algorithm-Based Token Optimization by Jinghui Jiang, Dongjoon Kim, Bohyoung Kim, Yeong-Gil Shin

“…This paper introduces GA-VAE, a fine-tuning framework that enhances local feature representation in pre-trained Vector Quantized-VAE (VQ-VAE) models through genetic algorithm-based optimization. …”
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An applied noise model for scintillation-based CCD detectors in transmission electron microscopy by Christian Zietlow, Jörg K. N. Lindner

“…Detectors usually suffer from gain non-linearities and quantum efficiency deviations, which must be corrected for optimal results. …”
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Space-Time Finite Element Tensor Network Approach for the Time-Dependent Convection–Diffusion–Reaction Equation with Variable Coefficients by Dibyendu Adak, Duc P. Truong, Radoslav Vuchkov, Saibal De, Derek DeSantis, Nathan V. Roberts, Kim Ø. Rasmussen, Boian S. Alexandrov

“…The effectiveness of the proposed method, in terms of memory efficiency and computational complexity, is demonstrated through a series of numerical experiments, including a semi-linear example.…”
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Two Images Watermarking by using Exponent Fourier Moments by LIU Xilin, HE Xianhao, ZHANG Hao, YUE Junhong, CHEN Zehua

“…Embedding a watermark into two images at one time is suggested to improve the efficiency of the watermarking procedure. [Methods] First, the two original images were combined together through complex representation, then the watermark was embedded by quantizing the magnitudes of the Exponent Fourier moments of the combined image, and the watermarked combined image was obtained by adding the combined image with the compensation image the was generated by reconstructing image from the modified Exponent Fourier moments. …”
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FPGA-accelerated mode decomposition for multimode fiber-based communication by Qian Zhang, Yuedi Zhang, Juergen Czarske

“…The FPGA’s customization and high efficiency provide substantial advantages, with low power consumption (2.4 Watts) and rapid inference (over 100 Hz), offering practical solutions for real-time applications. …”
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