Multidimensional State Data Reduction and Evaluation of College Students’ Mental Health Based on SVM by Han Peiqing

“…In response to the shortcomings of the traditional methods for evaluating the mental health status of college students in terms of computational complexity and low accuracy, a method for evaluating the mental health status of college students based on data reduction and support vector machines was proposed. …”
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A Method for Predicting Trajectories of Concealed Targets via a Hybrid Decomposition and State Prediction Framework by Zhengpeng Yang, Jiyan Yu, Miao Liu, Tongxing Peng, Huaiyan Wang

“…The RBMO further refines critical parameters within the ISVMD-ELM pipeline, ensuring adaptability and computational efficiency across diverse scenarios. …”
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ZZ-YOLOv11: A Lightweight Vehicle Detection Model Based on Improved YOLOv11 by Zhe Zhang, Zhongyang Zhang, Gang Li, Chenxi Xia

“…Secondly, to reduce the number of parameters in the detection head and to fuse the extracted features better, a self-developed Lightweight Detail Convolutional Detection Head (LDCD) detection head is introduced. …”
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A Transfer Learning Approach for Landslide Semantic Segmentation Based on Visual Foundation Model by Changhong Hou, Junchuan Yu, Daqing Ge, Liu Yang, Laidian Xi, Yunxuan Pang, Yi Wen

“…In addition, despite the transfer learning approach can transfer SAM feature extraction capability to the landslide segmentation task, but it will consume a lot of computational resources and training time. …”
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Research on dimension measurement algorithm for parcel boxes in high-speed sorting system by Ning Dai, Jingchao Chen, Xudong Hu, Yanhong Yuan

“…The high-low layer feature fusion structure and C2f-GhostCondConv are designed on the neck of the model to achieve the selective fusion of input features at different levels with small parameter number and computational amount. …”
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Research on RF Intensity Temperature Sensing based on 1D-CNN by DING Meiqi, GUI Lin, WANG Ziyi, SHANG Disen, QIAN Min, LI Qiankun

“…【Conclusion】1D-CNN has significant advantages in dealing with complex nonlinear relationships and feature extraction, not only superior in computational efficiency and robustness, but also effective in dealing with noise and environmental interference. …”
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Optimized exposer region-based modified adaptive histogram equalization method for contrast enhancement in CXR imaging by Shivam Gangwar, Reeta Devi, Nor Ashidi Mat Isa

“…The proposed PSO-ERBMAHE method delivers high-quality contrast enhancement in medical imaging, ensuring better visibility of critical anatomical features. By strengthening fine details, maintaining mean brightness, and improving computational efficiency, this technique enhances disease examination and diagnosis, reducing misinterpretation risks and improving clinical decision-making.…”
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Research on improving the ranging accuracy of ships with stereo vision through Kalman filter optimization. by Zhongbo Peng, Jie Han, Liang Tong, Lumeng Wang, Dan Liu, Shijie Sun

“…In the ship detection stage, addressing challenges such as large parameters, high computational complexity, and poor real-time performance in existing ship detection models, this paper proposes the MS-YOLOv5s ship target detection algorithm. …”
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Application of Quantum Recurrent Neural Network in Low-Resource Language Text Classification by Wenbin Yu, Lei Yin, Chengjun Zhang, Yadang Chen, Alex X. Liu

“…This architecture utilizes a pretrained multilingual bidirectional encoder representations from transformer (BERT) model to obtain vector representations of words and combines the proposed batch upload quantum recurrent neural network (BUQRNN) and parameter nonshared batch upload quantum recurrent neural network (PN-BUQRNN) as feature extraction models for sentiment analysis in Bengali. …”
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Intelligent assessment of damage and prediction of seismic damage spectrum under the effect of Near-Fault earthquakes in Iran by R. Fazli, M. Shamekhi Amiri, H. Pahlavan

“…Finally, a simplified equation has been suggested for assessing the potential seismic damage spectrum of the structures exposed to ground motions in Iran, capturing both structural and earthquake features. This study demonstrates the significant impact of structural and seismic parameters on the seismic damage spectrum, highlighting that an increase in the resistance reduction factor correlates with a rise in damage spectrum across structures of varying vibration periods. …”
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Detecting infrared UAVs on edge devices through lightweight instance segmentation. by YuZhi Chen, HaoYue Sun, Liang Tian, Ye Yang, ShenYang Wang, TianYou Wang

“…These architectural optimizations collectively reduce computational requirements while maintaining detection accuracy. …”
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Lightweight detection model for safe wear at worksites using GPD-YOLOv8 algorithm by Jian Xing, Chenglong Zhan, Jiaqiang Ma, Zibo Chao, Ying Liu

“…Firstly, this study introduces the P2 detection layer within the YOLOv8 architecture, which substantially enriches semantic feature representation. Additionally, a lightweight Ghost module is integrated to replace the original backbone of YOLOv8, thereby reducing the parameter count and computational burden. …”
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A lightweight algorithm for steel surface defect detection using improved YOLOv8 by Shuangbao Ma, Xin Zhao, Li Wan, Yapeng Zhang, Hongliang Gao

“…Firstly, GhostNet is utilized as the backbone network in order to reduce the number of model parameters and computational complexity. Secondly, the MPCA (MultiPath Coordinate Attention) attention mechanism is integrated to enhance feature extraction capabilities. …”
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Object Detection in High-Resolution UAV Aerial Remote Sensing Images of Blueberry Canopy Fruits by Yun Zhao, Yang Li, Xing Xu

“…We adopted a fast convolutional structure instead of the traditional convolutional structure, reducing the model’s parameter count and computational complexity. We proposed the PF-YOLO model and conducted experimental comparisons with several excellent models, achieving improvements in mAP of 5.5%, 6.8%, 2.5%, 2.1%, 5.7%, 2.9%, 1.5%, and 3.4% compared to Yolov5s, Yolov5l, Yolov5s-p6, Yolov5l-p6, Tph-Yolov5, Yolov8n, Yolov8s, and Yolov9c, respectively. …”
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Research on lightweight weed recognition algorithm based on improved YOLOv8 by Zhang Chao, Liu Bin, Li Kun

“…Aiming at the problems of low accuracy of current field weed identification models and the difficulty of deploying multiple parameters in mobile devices and embedded devices with limited computing resources, a lightweight field weed identification model based on YOLOv8 is proposed in this paper. …”
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A New Fault Detection and Classification Scheme in MTDC Grids with Hybrid Cable and Overhead Transmission Line by Zahra Moravej, Amir Imani, Mohammad Pazoki

“…In this paper, a new single-end time domain-based protection scheme for fault detection and classification is presented with remarkable features such as easy implementation, low computation burden, low sampling frequency, no setting parameters requirement, and also appropriate performance in noisy conditions. …”
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Infrared object detection for robot vision based on multiple focus diffusion and task interaction alignment by Jixu Zhang, Li Wang, Hung-Wei Li, Meng-Yen Hsieh, Shunxiang Zhang, Hua Wen, Meng Chen

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Development and evaluation of deep neural networks for the classification of subtypes of renal cell carcinoma from kidney histopathology images by Amit Kumar Chanchal, Shyam Lal, Shilpa Suresh

“…Additionally, the proposed method significantly reduces the number of parameters and FLOPs, demonstrating computationally efficient with 2.71 × $$10^9$$ FLOPs & 0.2131 × $$10^6$$ parameters.…”
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A One-Stage HMDV Algorithm Applied in Multitarget Detection in SAR Images by Lei Pang, Weihe Huang, Fengli Zhang, Yinhong Song

“…To tackle these issues, this article proposes a single-stage multi-target detection network called HMDV. First, a hybrid feature extraction module is designed to address the computational complexity caused by increased width and depth in convolutional neural networks. …”
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Multimodal Prompt-Guided Bidirectional Fusion for Referring Remote Sensing Image Segmentation by Yingjie Li, Weiqi Jin, Su Qiu, Qiyang Sun

“…Multimodal feature alignment is a key challenge in referring remote sensing image segmentation (RRSIS). …”
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