Quantum chimp-enanced SqueezeNet for precise diabetic retinopathy classification by Anas Bilal, Muhammad Shafiq, Waeal J. Obidallah, Yousef A. Alduraywish, Alishba Tahir, Haixia Long

“…The novel methodology was divided into two main stages: feature extraction and classification. Firstly, SqueezeNet enables efficient feature extraction from segmented fundus images with minimal computational complexity, ensuring that critical retinal features are captured effectively. …”
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Classification of left and right-hand motor imagery in acute stroke patients using EEG microstate by Shiyang Lv, Xiangying Ran, Mengsheng Xia, Yehong Zhang, Ting Pang, Xuezhi Zhou, Zongya Zhao, Yi Yu, Zhixian Gao

“…Four EEG microstate (A, B, C, and D) were analyzed to extract temporal feature parameters, including Duration, Occurrence Coverage, and transition probabilities(TP). …”
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GaitCSF: Multi-Modal Gait Recognition Network Based on Channel Shuffle Regulation and Spatial-Frequency Joint Learning by Siwei Wei, Xiangyuan Xu, Dewen Liu, Chunzhi Wang, Lingyu Yan, Wangyu Wu

“…Concurrently, the spatial domain processing branch balances the contributions of frequency and spatial domain information through an adaptive weighting mechanism, maintaining computational efficiency while enhancing features. Experimental results demonstrate that the proposed GaitCSF model achieves significant performance improvements on mainstream datasets including GREW, Gait3D, and SUSTech1k, breaking through the performance bottlenecks of traditional methods. …”
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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

“…Furthermore, with the increase of feature complexity and computation amount, the algorithm processing speed will be reduced. …”
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Gait stability prediction through synthetic time-series and vision-based data by Mauricio C. Cordeiro, Ciaran O. Cathain, Ciaran O. Cathain, Ciaran O. Cathain, Vitor B. Nascimento, Thiago B. Rodrigues

“…SHAP analysis revealed that the synthetic data approach enhanced feature attribution alignment with established principles, particularly for step width, BMI, and fall history.DiscussionTherefore, our results show that: (1) synthetic data accurately replicated gait parameters with high fidelity; (2) synthetic data-trained models outperformed real data-trained models in MoS prediction; and (3) step width, BMI, and fall history were the most significant predictors of MoS in older adults. …”
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YOLOLS: A Lightweight and High-Precision Power Insulator Defect Detection Network for Real-Time Edge Deployment by Qinglong Wang, Zhengyu Hu, Entuo Li, Guyu Wu, Wengang Yang, Yunjian Hu, Wen Peng, Jie Sun

“…Specifically, YOLOLS integrates GhostConv to generate feature maps through stepwise convolution, reducing computational redundancy while preserving representational capacity. …”
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Tiny-MobileNet-SE: A Hybrid Lightweight CNN Architecture for Resource-Constrained IoT Devices by Jean Pierre Nyakuri, Celestin Nkundineza, Omar Gatera, Kizito Nkurikiyeyezu

“…This architecture integrates Squeeze-and-Excitation (SE) blocks for adaptive feature recalibration, Batch Normalization (BN) for accelerated convergence, and applies knowledge distillation techniques from MobileNetV2 for enhanced feature generalization. …”
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Integrating high dimensional quadratic regression with penalties based predictive modeling for hydro power plants accurate tariff prediction by Ritesh Dash, Anupa Sinha, Abinash Mahapatro, Bhabasis Mohapatra, Binod Kumar Sahu

“…Compared to benchmarking models, the proposed approach consistently achieves the lowest forecast error. Computational complexity is minimized with 100 parameters and training time of 2 s. …”
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Learned Regularizations for Multi‐Parameter Elastic Full Waveform Inversion Using Diffusion Models by Mohammad H. Taufik, Fu Wang, Tariq Alkhalifah

“…Specifically, we first train the (unsupervised) diffusion model to understand the coupling relationship of the distribution of the elastic parameters and use the trained model in the inversion process with a negligible additional computational cost. …”
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Parametric Design of Railway Vehicle Axle Based on Secondary Development Technology of SolidWorks by 陈建, 米彩盈

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SkelETT—Skeleton-to-Emotion Transfer Transformer by Pedro Victor Vieira Paiva, Josue Junior Guimaraes Ramos, Marina Gavrilova, Marco Antonio Garcia de Carvalho

“…Emotion recognition plays an essential role in human-computer interaction, spanning diverse domains from human-robot communication and virtual reality to mental health assessment and affective computing. …”
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Ferroelectric Transistor-Based Synaptic Crossbar Arrays: The Impact of Ferroelectric Thickness and Device-Circuit Interactions by Chunguang Wang, Sumeet Kumar Gupta

“…Ferroelectric transistors (FeFETs)-based crossbar arrays have shown immense promise for computing-in-memory (CiM) architectures targeted for neural accelerator designs. …”
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Impaired intestinal calcium absorption and osteopathy in ICR/Mlac-hydro mice with hypoparathyroidism and severe hydronephrosis by Panan Suntornsaratoon, Kannikar Wongdee, Nithipak Thammayon, Jarinthorn Teerapornpuntakit, Nattapon Panupinthu, Wacharaporn Tiyasatkulkovit, Sarawut Lapmanee, Krittikan Chanpaisaeng, Surachai Chantip, Narattaphol Charoenphandhu

“…Ultra-high resolution micro-computed tomography further revealed defects in the trabecular bone microstructure, consistent with several abnormalities of bone histomorphometric parameters, e.g., reductions in osteoblast surface, active erosion surface, mineral apposition rate and bone formation rate. …”
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Vision transformer embedded video anomaly detection using attention driven recurrence by Ummay Maria Muna, Shanta Biswas, Syed Abu Ammar Muhammad Zarif, Philip Jefferson Deori, Tauseef Tajwar, Swakkhar Shatabda

“…Additionally, we incorporate a parameter-efficient recurrent model, the Simple Recurrent Unit Plus Plus (SRU++), which processes long sequential video embeddings efficiently by reducing computational costs by ten times compared to traditional methods. …”
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Corn-associated weed detection model based on WAAP-YOLO by Zhiyong MENG, Yawei JIA, Xiuqing ZHANG, Yongjing NI, Ming ZHANG, Qi WU, Chenxi WU

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Cephalometric characteristics of autochthonous population in the Republic of Kazakhstan by M. M. Soloviev, C. E. Ormanov, L. A. Aleksina, A. A. Baindurashvili

“…Front and side view photos of 320 Kazakh and Uzbek residents of Kazakhstan were studied by means of photo grammetry and a computer aided program «Harmony». Analysis of 46 cephalometric parameters resulted in the following findings: statistically significant difference between Uzbek and Kazakh males was detected in 39,1 % of the cases, while those among females were noted in 54,3 %, of the cases, i. e. ethnic distinctions were more pronounced in the females. …”
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Energy-efficient data routing using neuro-fuzzy based data routing mechanism for IoT-enabled WSNs by Sakthi Shunmuga Sundaram Paulraj, T. Deepa

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Estimation and Analysis of Sports Energy Consumption Based on Gait Tactile Parameters by Wang Yan, Zang Jian-Cheng, Li Bi-Tao

“…The combination of expectation-maximization algorithm and MapReduce computing model realizes the migration of traditional algorithm to “cloud computing” platform. …”
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Comparative Analysis of Classifiers for the Assessment of Respiratory Disorders Using Speech Parameters by Poonam Shrivastava, Neeta Tripathi, Bikesh Kumar Singh, Bhupesh Kumar Dewangan

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Stochastic Movement Swarm Performing a Coverage Task with Physical Parameters by Krzysztof FALKOWSKI, Michał DUDA

“…The lower the time interval, the more precise results, but simulating the test requires more computing power. Further work should consider the smallest possible time intervals or additional feature to check if the paths of the drones do not cross. …”
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