Research and Experiment on a Chickweed Identification Model Based on Improved YOLOv5s by Hong Yu, Jie Zhao, Xiaobo Xi, Yongbo Li, Ying Zhao

“…Currently, multi-layer deep convolutional networks are mostly used for field weed recognition to extract and identify target features. …”
Get full text

Two-stage Detection Method for Abnormal Cluster Cervical Cells by LIANG Yi-qin, ZHAO Si-qi, WANG Hai-tao, HE Yong-jun

“…In the first stage, we use YOLO-v5 target detection network. The standard convolution in the network is replaced by deformable convolution. …”
Get full text

FPGA-oriented lightweight multi-modal free-space detection network by Feiyi Fang, Junzhu Mao, Wei Yu, Jianfeng Lu

“…With the development of multi-modal convolutional neural networks (CNNs) in recent years, the performance of driving scene semantic segmentation algorithms has been dramatically improved. …”
Get full text

Prediction of mechanical characteristics of shearer intelligent cables under bending conditions. by Lijuan Zhao, Dongyang Wang, Guocong Lin, Shuo Tian, Hongqiang Zhang, Yadong Wang

“…This paper proposes a shearer optical fiber cable mechanical characteristics prediction model based on Temporal Convolutional Network (TCN), Bidirectional Long Short-Term Memory (BiLSTM), and Squeeze-and-Excitation Attention (SEAttention), referred to as the TCN-BiLSTM-SEAttention model. …”
Get full text

Underground helmet detection algorithm based on improved YOLOv8s by Jiaru YANG, Yinan QIN, Tianxu LI, Han ZHUANG

“…In the process of coal mine underground operation, the safety helmet is the most direct and effective protective measure, and it is an important measure to ensure the safety of miners. …”
Get full text

IDNet: An inception-like deformable non-local network for projection compensation over non-flat textured surfaces. by Yuqiang Zhang, Huamin Yang, Cheng Han, Chao Zhang, Chao Xu, Shiyu Lu

“…Projector compensation on non-flat, textured surfaces represents a formidable challenge in computational imaging, with conventional convolution-based methods frequently encountering critical limitations, especially in image edge regions characterized by complex geometric transformations. …”
Get full text

Airport Clearance Detection Based on Vision Transformer and Multi-Scale Feature Fusion by Yutong Chen, Yufen Liu, Zhixiong Guo, Qiang Gao

“…Secondly, to improve the feature extraction ability, partial convolution is replaced with dynamic convolution, and attention is introduced to the convolution kernel from four dimensions. …”
Get full text

Collective cell migration drives morphogenesis of the kidney nephron. by Aleksandr Vasilyev, Yan Liu, Sudha Mudumana, Steve Mangos, Pui-Ying Lam, Arindam Majumdar, Jinhua Zhao, Kar-Lai Poon, Igor Kondrychyn, Vladimir Korzh, Iain A Drummond

“…Complete blockade of pronephric fluid flow prevented cell migration and proximal nephron convolution. Selective blockade of proximal, filtration-driven fluid flow shifted the position of tubule convolution distally and revealed a role for cilia-driven fluid flow in persistent migration of distal nephron cells. …”
Get full text

HMA-Net: a hybrid mixer framework with multihead attention for breast ultrasound image segmentation by Soumya Sara Koshy, L. Jani Anbarasi

“…IntroductionBreast cancer is a severe illness predominantly affecting women, and in most cases, it leads to loss of life if left undetected. …”
Get full text

Deep Learning-Based Ground-Penetrating Radar Inversion for Tree Roots in Heterogeneous Soil by Xibei Li, Xi Cheng, Yunjie Zhao, Binbin Xiang, Taihong Zhang

“…Additionally, a GPR simulation data set and a measured data set are built in this study, which were used to train inversion models and validate the effectiveness of GPR inversion methods.The introduced GPR inversion model is a pyramid convolutional network with vision transformer and edge inversion auxiliary task (PyViTENet), which combines pyramidal convolution and vision transformer to improve the diversity and accuracy of data feature extraction. …”
Get full text

An automatic modulation recognition network based on multi-channel lightweighting by WAN Jinhua, SHANG Junna, ZHANG Huadi

“…Existing automatic modulation recognition models perform well in recognition accuracy, but most methods have difficulty in achieving an ideal balance between the number of parameters and model performance. …”
Get full text

Virtual Reality Video Image Classification Based on Texture Features by Guofang Qin, Guoliang Qin

“…As one of the most widely used methods in deep learning technology, convolutional neural networks have powerful feature extraction capabilities and nonlinear data fitting capabilities. …”
Get full text

Noise-Robust Local Ternary Pattern Center for Noisy Texture Classification by Farhan A. Alenizi, Mokhtar Mohammadi, Mohammad Hossein Shakoor

“…The more level of noise the more number of applying average kernel must be convolved to each texture. Convolution is a time-consuming operation, so here, a fast average method is proposed that can do this operation around 2 to 3 times faster than the traditional convolution method. …”
Get full text

A Deep Reinforcement Learning Approach for Portfolio Management in Non-Short-Selling Market by Ruidan Su, Chun Chi, Shikui Tu, Lei Xu

“…Reinforcement learning (RL) has been applied to financial portfolio management in recent years. Current studies mostly focus on profit accumulation without much consideration of risk. …”
Get full text

An Accelerated FPGA-Based Parallel CNN-LSTM Computing Device by Xin Zhou, Wei Xie, Han Zhou, Yongjing Cheng, Ximing Wang, Yun Ren, Shandong Yuan, Liuwen Li

“…Recently, the combination of convolutional neural network (CNN) and long short-term memory (LSTM) exhibits better performance than single network architecture. …”
Get full text

Academic Emotion Classification Using FER: A Systematic Review by Jeniffer Xin-Ying Lek, Jason Teo

“…Moreover, support vector machine (SVM) is the conventional learning emotion classifier that is widely used in the FER systems, while convolutional neural network (CNN) is the most frequently used deep learning classifier. …”
Get full text

Detection Method for Bolts with Mission Pins on Transmission Lines Based on DBSCAN-FPN by Zhenbing ZHAO, Shuai ZHANG, Wei JIANG, Peng WU

“…Bolts are the mostly used fasteners on transmission lines, and their defect detection is an important content for transmission line inspection. …”
Get full text

A Novel Pseudo-Siamese Fusion Network for Enhancing Semantic Segmentation of Building Areas in Synthetic Aperture Radar Images by Mengguang Liao, Longcheng Huang, Shaoning Li

“…Compared to traditional methods, deep learning-driven approaches exhibit superiority in the aspect of stability and efficiency. Currently, most segmentation methods use a single neural network to encode SAR images, then decode them through interpolation or transpose convolution operations, and finally obtain the segmented building area images using a loss function. …”
Get full text

YOLO-RDM: A high accuracy and efficient algorithm for magnetic tile surface defect detection with practical applications. by Wei Niu, Cheng Lv, Enxu Zhang, Zhongbin Wei

“…By using a lightweight convolution method, we replace the traditional convolution in the original network, thereby improving the feature extraction ability of the model and achieving lightweight processing. …”
Get full text

Neural network analysis of small samples using a large number of statistical criteria to test the sequence of hypotheses about the value of mathematical expectations of correlation... by A.I. Ivanov, A.I. Godunov, E.A. Malygina, N.A. Papusha, A.I. Ermakova

“…The correlation coefficient is one of the most significant second-order statistical points. …”