Cervical Cell Nuclear Segmentation Method Based on Optimized MSER Algorithm by HE Yong jun, ZHANG Xue yuan, SHAO Hui li, DING Bo

Get full text

Prediction of Right Heart Failure in LVAD Candidates: Current Approaches and Future Directions by Frederick Vogel, Zachary W. Sollie, Arman Kilic, Ethan Kung

Get full text

SD-YOLOv5: a rapid detection method for personal protective equipment on construction sites by ChunYa Li, ChunYa Li, Jianhua Wang, Jianhua Wang, Bingfeng Luo, Tubing Yin, Baohua Liu, Baohua Liu, Jianfei Lu

“…The proposed model incorporates a dedicated feature layer for small target detection and integrates the DilateFormer attention mechanism to balance detection performance and computational efficiency. …”
Get full text

An Analytical Framework for Risk Evaluation and Design of Infiltration Basins for Managed Aquifer Recharge by Aldo Fiori, Felipe P. J. de Barros, Alberto Bellin

“…Although the framework relies on simplifying assumptions, it provides a computationally efficient manner to obtain physical insights and relate model input parameters to decision making.…”
Get full text

Variability of morphometric traits of seeds of different genotypes of Lycium spp. by M. Yu. Zhurba, S. V. Klymenko, Iwona Szot

“…The analysis of coefficient of variation showed the difference of variability in morphometric characteristics between some Lycium spp. cultivars and varieties. The most variable features: seeds weight (8.51–28.22%) and seeds length (5.07–24.81%) are important parameters for selection. …”
Get full text

Abnormal gait recognition with millimetre‐wave radar based on perceptual loss and convolutional temporal autoencoder by Peng Zhao, Ling Hong, Yu Wang

Get full text

A Chinese Few-Shot Named-Entity Recognition Model Based on Multi-Label Prompts and Boundary Information by Cong Zhou, Baohua Huang, Yunjie Ling

Get full text

A Dynamic Inverse Decoupling Control Method for Reducing Energy Consumption in a Quadcopter UAV by Guoxin Ma, Kang Tian, Hongbo Sun, Yongyan Wang, Haitao Li

Get full text

Optimizing Artificial Neural Networks Using Mountain Gazelle Optimizer by Muhammed Abdulhamid Karabiyik, Bahaeddin Turkoglu, Tunc Asuroglu

Get full text

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. …”
Get full text

Output Feedback Adaptive Dynamic Surface Sliding-Mode Control for Quadrotor UAVs with Tracking Error Constraints by Guoqiang Zhu, Sen Wang, Lingfang Sun, Weichun Ge, Xiuyu Zhang

“…The framework of the controller design process is divided into two stages: the attitude control process and the position control process. The main features of this work are (1) a nonlinear observer is employed to predict the motion velocities of the quadrotor UAV; therefore, only the position signals are needed for the position tracking controller design; (2) by using the minimum learning technology, there is only one parameter which needs to be updated online at each design step and the computational burden can be greatly reduced; (3) a performance function is introduced to transform the tracking error into a new variable which can make the tracking error of the system satisfy the prescribed performance indicators; (4) the sliding-mode surface is introduced in the process of the controller design, and the robustness of the system is improved. …”
Get full text

Quantitative Analysis of Conjunctival and Retinal Vessels in Fabry Disease by Andrea Sodi, Chiara Lenzetti, Daniela Bacherini, Lucia Finocchio, Tommaso Verdina, Isabella Borg, Francesca Cipollini, Fatema Ullah Patwary, Ilaria Tanini, Claudia Zoppetti, Stanislao Rizzo, Gianni Virgili

“…It has been described an increasing in retinal and conjunctival vessel tortuosity and this feature represents an important marker for the disease. …”
Get full text

An Enhanced Deep Learning Model for Effective Crop Pest and Disease Detection by Yongqi Yuan, Jinhua Sun, Qian Zhang

“…By replacing the standard convolutions in ResNet34 with depthwise separable convolutions, the model reduces its parameter count by 85.37% and its computational load by 84.51%. …”
Get full text

High performance adaptive step size fractional numerical scheme for solving fractional differential equations by Mudassir Shams, Ahmad Alalyani

“…These equations provide a powerful framework for describing phenomena with memory effects and hereditary features that standard integer-order models cannot account for. …”
Get full text

AMD-FV: Adaptive margin loss and dual path network+ for deep face verification. by Zeeshan Ahmed Khan, Waqar Ahmed, Panos Liatsis

“…Input dissimilarity information is used to estimate the margin, while the scale parameter is computed using the number of classes and AML's range. …”
Get full text

TCE-YOLOv5: Lightweight Automatic Driving Object Detection Algorithm Based on YOLOv5 by Han Wang, Zhenwei Yang, Qiaoshou Liu, Qiang Zhang, Honggang Wang

“…Firstly, the Bottleneck convolution kernel channels in the C3 module were grouped to greatly reduce the number of parameters. Secondly, the C3 module in the neck is replaced by the Res2Net module, which extracts features at different scales through multiple branches, not only ensuring rich details, but also enhancing the generalization ability of the network. …”
Get full text

Deep Neural Emulation of the Supermassive Black Hole Binary Population by Nima Laal, Stephen R. Taylor, Luke Zoltan Kelley, Joseph Simon, Kayhan Gültekin, David Wright, Bence Bécsy, J. Andrew Casey-Clyde, Siyuan Chen, Alexander Cingoranelli, Daniel J. D’Orazio, Emiko C. Gardiner, William G. Lamb, Cayenne Matt, Magdalena S. Siwek, Jeremy M. Wachter

“…As a result, we can predict strain distributions that mirror underlying simulations very closely while also capturing frequency covariances in the strain distributions as well as statistical complexities such as tails, non-Gaussianities, and multimodalities that are otherwise not learnable by existing techniques. In particular, we feature various comparisons between the NF-based emulator and the GP approach used extensively in past efforts. …”
Get full text

Copper Nodule Defect Detection in Industrial Processes Using Deep Learning by Zhicong Zhang, Xiaodong Huang, Dandan Wei, Qiqi Chang, Jinping Liu, Qingxiu Jing

“…The model employs MobileNetV3, a lightweight feature extraction network, as its backbone, reducing the parameter count and computational complexity. …”
Get full text

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. …”
Get full text

Leveraging Vision Foundation Model via PConv-Based Fine-Tuning with Automated Prompter for Defect Segmentation by Yifan Jiang, Jinshui Chen, Jiangang Lu

“…The Segment Anything Model (SAM) has shown exceptional performance across various downstream tasks, owing to its vast semantic knowledge and strong generalization capabilities. However, the feature distribution discrepancy, reliance on manually labeled prompts, and limited category information of SAM reduce its scalability in industrial settings. …”
Get full text