Advanced retinal disease detection from OCT images using a hybrid squeeze and excitation enhanced model. by Gülcan Gencer, Kerem Gencer

“…EfficientNetB0 achieves high accuracy with fewer parameters through model scaling strategies, while Xception offers powerful feature extraction using deep separable convolutions. …”
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Improvement of RT-DETR model for ground glass pulmonary nodule detection. by Siyuan Tang, Qiangqiang Bao, Qingyu Ji, Tong Wang, Naiyu Wang, Min Yang, Yu Gu, Jinliang Zhao, Yuhan Qu, Siriguleng Wang

“…To obtain a more lightweight model, modules are designed for smaller number of parameters and higher computational efficiency. Model are tested on mixed dataset composed of LIDC-IDRI data and clinical data from cooperating hospitals. …”
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Comparing Grid Model Fitting Methodologies for Low-temperature Atmospheres: Markov Chain Monte Carlo versus Random Forest Retrieval by Anna Lueber, Adam J. Burgasser

“…Self-consistent atmosphere models are commonly used for spectral fitting, but computational limits restrict the production of finely sampled multidimensional parameter grids, necessitating interpolation methods to infer precise parameters and uncertainties. …”
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Contrast Limited Adaptive Local Histogram Equalization Method for Poor Contrast Image Enhancement by Ibrahim Majid Mohammed, Nor Ashidi Mat Isa

“…Third, the original image is divided into subimages, and the optimal parameters are applied to each subimage independently, emphasizing and enhancing local features. …”
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Robust radiogenomics approach to the identification of EGFR mutations among patients with NSCLC from three different countries using topologically invariant Betti numbers. by Kenta Ninomiya, Hidetaka Arimura, Wai Yee Chan, Kentaro Tanaka, Shinichi Mizuno, Nadia Fareeda Muhammad Gowdh, Nur Adura Yaakup, Chong-Kin Liam, Chee-Shee Chai, Kwan Hoong Ng

“…Forty-one cases collected from the Kyushu University Hospital (KUH) in Japan and fifty-four cases obtained from The Cancer Imaging Archive (TCIA) in America were used for a test procedure. Radiomic features were obtained from BN maps, which represent topologically invariant heterogeneous characteristics of lung cancer on CT images, by applying histogram- and texture-based feature computations. …”
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Lightweight insulator target detection algorithm based on improved YOLOX by Bing Zeng, Wei Hua, Dezhi Li, Zhihao Zhou, Hao Wan, Yunmin Xie, Tangbing Li, Yucong Chen, Jianglei Li, Shenli Wang, Shixun Fu, Zihan Jin, Wenhua Zhang

“…Experiments show that compared to the original YOLOX, the proposed algorithm reduces parameters by 53.41% to 4.164 M and computational load to 12.975G, with mAP increased by 1.3%, detection accuracy reaching 98.81%, and recall achieving 100%. …”
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Neural Mass Modeling in the Cortical Motor Area and the Mechanism of Alpha Rhythm Changes by Yuanyuan Zhang, Zhaoying Li, Hang Xu, Ziang Song, Ping Xie, Penghu Wei, Guoguang Zhao

“…Finally, model parameters were adjusted to achieve feature fitting between the simulated signals and the average power of the alpha rhythm. …”
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YOLO-Pika: a lightweight improved model of YOLOv8n incorporating Fusion_Block and multi-scale fusion FPN and its application in the precise detection of plateau pikas by Yihao Liu, Jianyun Zhao, Changjun Xu, Yuedi Hou, Yuxiang Jiang

“…We propose YOLO-Pika, a lightweight detector built on YOLOv8n that integrates (1) a Fusion_Block into the backbone, leveraging high-dimensional mapping and fine-grained gating to enhance feature representation with negligible computational overhead, and (2) an MS_Fusion_FPN composed of multiple MSEI modules for multi-scale frequency-domain fusion and edge enhancement. …”
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A study on the prediction of mountain slope displacement using a hybrid deep learning model by Yuyang Ma, Xiangxiang Hu, Yuhang Liu, Yaya Shi, Zhiyuan Yu, Xinmin Wang, Liangbai Hu, Shuailing Liu, Dongdong Pang

“…The method employs an Improved Whale Optimization Algorithm (IWOA) to fine-tune parameters for GNSS data fitting, ensuring accurate signal feature extraction. …”
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Numerical and experimental investigation of piezoelectric-pneumatic material jet printing method for high-viscosity ink by Xinyi Hu, Xiaoran Dong, Zhanda Li, Junhui Long, Yuan Jin, Hui Li

“…In this work, a two-dimensional computational fluid dynamics model is presented to elucidate the multiphase aerodynamic phenomenon and deposition morphology of jet printing features. …”
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URT-YOLOv11: A Large Receptive Field Algorithm for Detecting Tomato Ripening Under Different Field Conditions by Di Mu, Yuping Guou, Wei Wang, Ran Peng, Chunjie Guo, Francesco Marinello, Yingjie Xie, Qiang Huang

“…These factors often hinder accurate feature extraction, leading to recognition errors and reduced computational efficiency. …”
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Investigation of Geometric Characteristics on the Lubricant Performance of Thrust Bearing with Cavitation by L. Kailei, C. Jiayuan, Z. Haoran, Z. Lin, W. Xuze, C. Yu

“…The simulation model considers the impact of geometric characteristics and operational conditions, including the viscoelastic effect, transformation feature, and flow state, to enhance calculation ability. …”
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One-Dimensional Deep Residual Network with Aggregated Transformations for Internet of Things (IoT)-Enabled Human Activity Recognition in an Uncontrolled Environment by Sakorn Mekruksavanich, Anuchit Jitpattanakul

“…We developed a comprehensive network that utilizes feature fusion and a multi-kernel block approach. …”
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Improved deep learning method and high-resolution reanalysis model-based intelligent marine navigation by Zeguo Zhang, Zeguo Zhang, Zeguo Zhang, Liang Cao, Liang Cao, Liang Cao, Jianchuan Yin, Jianchuan Yin, Jianchuan Yin

“…Key components include: (1) IPCA preprocessing to reduce dimensionality and noise in 2D wind field data; (2) depthwise-separable convolution (DSC) blocks to minimize parameters and computational costs; (3) multi-head attention (MHA) and residual mechanisms to improve spatial-temporal feature extraction and prediction accuracy. …”
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A One-Dimensional Depthwise Separable Convolutional Neural Network for Bearing Fault Diagnosis Implemented on FPGA by Yu-Pei Liang, Hao Chen, Ching-Che Chung

“…The design processes the one-dimensional rolling bearing current signal dataset provided by Paderborn University (PU), employing minimal preprocessing to maximize the comprehensiveness of feature extraction. To address the high parameter demands commonly associated with convolutional neural networks (CNNs), the model incorporates DSC, significantly reducing computational complexity and parameter load. …”
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Dynamic equivalent modelling for active distributed network considering adjustable loads charging characteristics by Jingwen Wang, Jiehui Zheng, Zhigang Li, Qing‐Hua Wu

“…Subsequently, a four‐layer, tri‐stage deep reinforcement learning approach is used to solve the relevant key parameters of the proposed equivalent model. The method proposed in this paper fully utilizes the superiority of reinforcement learning in decision making, while the method combines the excellent feature extraction capability of deep learning. …”
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FL-DBENet: Double-branch encoder network based on segment anything model for farmland segmentation of large very-high-resolution optical remote sensing images by W. Feng, F. Guan, C. Sun, W. Xu, W. Xu

“…To further streamline the model, we integrate a Low-Rank Adaptation (LoRA) module into SAM’s image encoder, reducing training parameters and computational demands. Additionally, a prompt mixer module is developed to integrate diverse features effectively. …”
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Combining graph neural network and Mamba to capture local and global tissue spatial relationships in whole slide images by Ruiwen Ding, Kha-Dinh Luong, Erika Rodriguez, Ana Cristina Araujo Lemos da Silva, William Hsu

“…Abstract In computational pathology, extracting and representing spatial features from gigapixel whole slide images (WSIs) are fundamental tasks, but due to their large size, WSIs are typically segmented into smaller tiles. …”
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Research on Laser Radar Inspection Station Planning of Vehicle Body-In-White (BIW) with Complex Constraints by Lijuan Li, Siyi Wang, Jichao Ma, Xiaobing Gao

“…Firstly, a parametric geometric modeling approach is developed to define measurement spaces for individual features, accompanied by an innovative maximal complete subgraph mining algorithm to intelligently identify shared feasible measurement regions among multiple features. …”
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RETRACTED: Intelligent power grid energy supply forecasting and economic operation management using the snake optimizer algorithm with Bigur-attention model by Lingling Cui, Jiacheng Liao

“…The model evaluation phase calculates metrics such as prediction error, accuracy, and stability, and also examines the model’s training time, inference time, number of parameters, and computational complexity to assess its efficiency and scalability. …”
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