Prognostic and therapeutic potential of disulfidptosis-related genes in colon adenocarcinoma: a comprehensive multi-omics study by Ye Song, Haoran Zhu, Junyang Wei, Shanxue Yin

“…The ProjecTILs algorithm identified a higher proportion of Th1 cells, while Graph Convolutional Network (GCN) analysis showed no significant differences in T cell subtype proportions across different phenotypes. …”
Get full text

Prediction of Shield Tunneling Attitude Based on WM-CTA Method by GAO Su, CHEN Cheng

“…The preprocessing module, composed of Wavelet Transform (WT) and the Maximum Information Coefficient (MIC) algorithms, was used to perform noise reduction and parameter correlation analysis on the raw data, thereby generating enhanced inputs. The Convolutional Neural Network (CNN) integrated with a channel-wise attention mechanism explored parameter weight differences and extracted local data features. …”
Get full text

Global Ionospheric TEC Map Prediction Based on Multichannel ED-PredRNN by Haijun Liu, Yan Ma, Huijun Le, Liangchao Li, Rui Zhou, Jian Xiao, Weifeng Shan, Zhongxiu Wu, Yalan Li

“…The proposed Multichannel ED-PredRNN was compared with COPG, ConvLSTM, and convolutional gated recurrent unit (ConvGRU) from multiple perspectives on a data set of 6 years, including comparisons at different solar activities, time periods, latitude regions, single stations, and geomagnetic storm periods. …”
Get full text

Feature Selection-Based Hierarchical Deep Network for Image Classification by Guiqing He, Jiaqi Ji, Haixi Zhang, Yuelei Xu, Jianping Fan

“…In this paper, a novel hierarchical deep network is proposed to combine the deep convolutional neural network and the feature selection-based tree classifier efficiently for image classification. …”
Get full text

Spherical harmonics texture extraction for versatile analysis of biological objects. by Oane Gros, Josiah B Passmore, Noa O Borst, Dominik Kutra, Wilco Nijenhuis, Timothy Fuqua, Lukas C Kapitein, Justin M Crocker, Anna Kreshuk, Simone Köhler

“…The characterization of phenotypes in cells or organisms from microscopy data largely depends on differences in the spatial distribution of image intensity. …”
Get full text

Super-resolution reconstruction technology for full-diameter core nuclear magnetic resonance scanning data: a global non-negative least squares-based approach by Yingying MA, Zebo PENG, Jingzhi CHEN, Fei WU, Xin NIE, Zhongshu LIAO, Gong ZHANG

“…However, due to its large measurement sensitivity area, signals from different positions overlap, resulting in a significantly lower vertical resolution compared to instrument sampling. …”
Get full text

FD²-YOLO: A Frequency-Domain Dual-Stream Network Based on YOLO for Crack Detection by Junwen Zhu, Jinbao Sheng, Qian Cai

“…Furthermore, the Dynamic Inter-Domain Feature Fusion module (DIFF) is introduced, which uses large-kernel deep convolution and Hadamard to enable the adaptive fusion of features from different domains, thus addressing the problem of difficult feature fusion due to domain differences. …”
Get full text

MCPA: multi-scale cross perceptron attention network for 2D medical image segmentation by Liang Xu, Mingxiao Chen, Yi Cheng, Pengwu Song, Pengfei Shao, Shuwei Shen, Peng Yao, Ronald X. Xu

“…Abstract The UNet architecture, based on convolutional neural networks (CNN), has demonstrated its remarkable performance in medical image analysis. …”
Get full text

Feasibility of the Anchor-Free Deep Learning Method in Coronary Stenosis Automatic Detection by Hanlin Yue, Wei Yu, Ji Dong, Yunfei Lai, You Wu, Haixia Zhao, Yiwei Song, Li Zhao, Hui Wang, Jing Zhang, Xinping Xu, Binwei Yao, Jianghao Zhao, Kexian Wang, Yue Sun, Haoyu Wang, Ruiyun Peng

“…The main purpose of this paper was to investigate the feasibility of an anchor-free deep learning (DL) method, fully convolutional one-stage object detection (FCOS), in coronary artery stenosis automatic detection. …”
Get full text

Research on Upper Limb Motion Intention Classification and Rehabilitation Robot Control Based on sEMG by Tao Song, Kunpeng Zhang, Zhe Yan, Yuwen Li, Shuai Guo, Xianhua Li

“…To avoid the drawbacks of modeling methods, traditional machine learning and deep learning methods are employed to perform a nine-class classification task on the sEMG data, comparing the classification accuracy of different approaches. Finally, the motor intentions extracted using a multi-stream convolutional neural network (MLCNN) are utilized to control the iReMo^® end-effector rehabilitation robot, with the system’s motion smoothness and accuracy evaluated through tests involving different trajectories.…”
Get full text

An Explainable Model Using Graph-Wavelet for Predicting Biophysical Properties of Proteins and Measuring Mutational Effects by Shreya Mishra, Neetesh Pandey, Atul Rawat, Divyanshu Srivastava, Arjun Ray, Vibhor Kumar

“…Proteins hold multispectral patterns of different kinds of physicochemical features of amino acids in their structures, which can help understand proteins’ behavior. …”
Get full text

Pretraining-improved Spatiotemporal graph network for the generalization performance enhancement of traffic forecasting by Xiangyue Zhang, Chao Li, Ling Ji, Yuyun Kang, Mingming Pan, Zhuo Liu, Qiang Qi

“…To address these issues, various sophisticated modules are embedded into different models. However, this approach increases the computational cost of the model. …”
Get full text

An Ultrafast Image Simulation Technique with Spatially Variable Point-spread Functions by Zeyu Bai, Peng Jia, Jiameng Lv, Xiang Zhang, Wennan Xiang, Lin Nie

“…Although widely used, these approaches suffer from slow convolution processes and reduced image fidelity due to abrupt PSF transitions between different patches. …”
Get full text

Meteorological measurement and simulation datasets to understand the complex circulation over a tropical inter-Andean valleyMendeley Data by Andres V. Ardila, Carlos M. González, Felipe Cifuentes, German Rueda-Saa, Rodrigo Jimenez

“…Atmospheric circulation over tropical mountainous regions is intrinsically complex, and frequently difficult to reproduce in simulation models, due to the convolution of synoptic, mesoscale, local convective, and topographically induced effects. …”
Get full text

Semantic segmentation of substation tools using an improved ICNet network by Guozhong Liu, Qiongping Tang, Changnian Lin, An Xu, Chonglong Lin, Hao Meng, Mengyu Ruan, Wei Jin

“…A lightweight backbone network was used in the feature extraction stage at different resolutions, and a recursive gated convolution was used in the upsampling stage to achieve high-order spatial interactions, thereby improving segmentation accuracy. …”
Get full text

Online Calibration Method of LiDAR and Camera Based on Fusion of Multi-Scale Cost Volume by Xiaobo Han, Jie Luo, Xiaoxu Wei, Yongsheng Wang

“…In addition, due to the large domain differences between different public datasets, the existing online calibration algorithms are unstable for various datasets and have poor algorithm robustness. …”
Get full text

Classification of Buried Objects From Ground Penetrating Radar Images by Using Second-Order Deep Learning Models by Douba Jafuno, Ammar Mian, Guillaume Ginolhac, Nickolas Stelzenmuller

“…We also illustrate the interest of our models when training data and test sets are obtained from different weather modes or considerations.…”
Get full text

A Hierarchical and Self-Evolving Digital Twin (HSE-DT) Method for Multi-Faceted Battery Situation Awareness Realisation by Kai Zhao, Ying Liu, Yue Zhou, Wenlong Ming, Jianzhong Wu

“…Its hierarchical structure allows the integration of different estimation models, and the self-evolving method allows the method to adapt to changes in different operating conditions. …”
Get full text

Large-Scale nighttime illuminated road extraction in the BTH region of China using SDGSAT-1 nighttime light data by Qiyuan Xie, Hui Li, Linhai Jing, Yichen Jiang, Haifeng Ding, Zhongchang Sun

“…The assessment results revealed an imbalance in road lighting levels among different cities in the BTH region.…”
Get full text

Biomimetic Visual Information Spatiotemporal Encoding Method for In Vitro Biological Neural Networks by Xingchen Wang, Bo Lv, Fengzhen Tang, Yukai Wang, Bin Liu, Lianqing Liu

“…This method transforms high-dimensional images into a series of pulse sequences through convolution, temporal delay, alignment, and compression for BNN stimuli. …”
Get full text