Dual-Branch Deep Learning with Dynamic Stage Detection for CT Tube Life Prediction by Zhu Chen, Yuedan Liu, Zhibin Qin, Haojie Li, Siyuan Xie, Litian Fan, Qilin Liu, Jin Huang

Get full text

An Attention-Based Spatial-Spectral Joint Network for Maize Hyperspectral Images Disease Detection by Jindai Liu, Fengshuang Liu, Jun Fu

“…However, the abundance of redundant information in hyperspectral data poses challenges in extracting significant features. To overcome the above problems, in this study we proposed an attention-based spatial-spectral joint network model for hyperspectral detection of pest-infected maize. …”
Get full text

Research on the detection of obstacles in front of unmanned vehicles in opencast mines based on binocular vision by Shunling RUAN, Huiguo ZHANG, Qinghua GU, Caiwu LU, Di LIU, Jing MAO

“…The Feffol network model proposed in this paper selects Efficient-v2 as the backbone network structure for feature extraction in the feature extraction stage, selects the Ebifpn feature pyramid module based on the SppCSP structure with SppCSP structure to improve the feature sensing field while enhancing the feature information of different sizes, uses the Focal Loss and CIoU Loss loss functions to balance positive and negative samples, and solve the problem of method failure when there is no intersection between the prediction frame and the real detection frame. …”
Get full text

DETECTION OF TEXT OBJECTS IN IMAGES OF REAL SCENES BASED ON CONVOLUTIONAL NEURAL NETWORK MODEL by N. N. Kuzmitsky

Get full text

Weighted Feature Fusion Network Based on Large Kernel Convolution and Transformer for Multi-Modal Remote Sensing Image Segmentation by Jianxia Wang, Shaozu Qiu, Jia Cai, Xiaoming Zhang

“…Finally, a Difference information Feature Fusion Module (DFFM) leveraging attention to differential regions is used to achieve cross-level feature fusion and enhance small object detection. …”
Get full text

AnoViT: Unsupervised Anomaly Detection and Localization With Vision Transformer-Based Encoder-Decoder by Yunseung Lee, Pilsung Kang

“…Image anomaly detection problems aim to determine whether an image is abnormal, and to detect anomalous areas. …”
Get full text

Research on Breast Cancer Detection Methods Based on ODMV-MulDyHead-YOLO by Yanhong Zhang, Pei Li, Yihua Lan, Xiao Jia, Yingjie Lv

“…In this paper, we proposed a method of breast cancer detection based on full-dimensional dynamic convolution and multiple attention mechanism to solve the problems of missing detection and low detection accuracy caused by breast tumor occlusion by breast muscle, poor contrast between tumor and surrounding glandular tissue and indistinct features of small tumor. …”
Get full text

FsDAOD: Few-shot domain adaptation object detection for heterogeneous SAR image by Siyuan Zhao, Yong Kang, Hang Yuan, Guan Wang, Hui Wang, Shichao Xiong, Ying Luo

“…In which the small sample of data scarcity is becoming an urgent problem for researchers. Therefore, this paper proposes a novel few-shot domain adaptation object detection (FsDAOD) method based on Faster Region Convolutional Neural Network baseline to cope with the above problem. …”
Get full text

TomaFDNet: A multiscale focused diffusion-based model for tomato disease detection by Rijun Wang, Rijun Wang, Yesheng Chen, Fulong Liang, Xiangwei Mou, Xiangwei Mou, Guanghao Zhang, Hao Jin

“…MethodsThe multi-scale tomato leaf disease detection model Tomato Focus-Diffusion Network (TomaFDNet) was proposed to solve the above problems. …”
Get full text

Improved M-ORB based direct-loop closure detection algorithm for visual SLAM by Wei LI, Menghan REN, Weihao HUANG, Xiaoyu DU, Yi ZHOU

“…Most kinds of direct methods do not extract image feature points in the front end of SLAM system, resulting in that they cannot use loop closure detection with bag-of-words models to eliminate the cumulative error of the system.To resolve this problem, an improved mature-oriented fast and rotated BRIEF (M-ORB) based direct-loop closure detection algorithm for visual SLAM was proposed, which designed an improved M-ORB, generated the bag of words model required for loop closure detection, and then used the term frequency-inverse document frequency (TF-IDF) algorithm to adaptively assign weights to the visual words in each sub-node of the dictionary tree.Finally, an accurate representation of the scene information was obtained.In the end, the proposed algorithm and conducted comparative experiments were verified though two public data sets TUM and KITTI.The experimental results show that the algorithm proposed in this paper can effectively detect the loop closure, and has better real-time and robustness performance without reducing the accuracy.…”
Get full text

Intelligent Rail Flaw Detection System Based on Deep Learning and Support Vector Machine by Jiangping LUO, Xizhuo YU, Jingwei CAO, Weihong DU

“…Currently, detection systems of rail flaw detection vehicles in China have automatic flaw recognition function, which has problems with low accuracy, high false alarm rate and occurrence of underreport because of the adoption of simple logic judgment method based on the existing rules. …”
Get full text

Safety belt wearing detection for electric aloft work based on EPSA-YOLOv5 by LI Yongfu, CHEN Libin, HUI Junwei, YUAN Runcong, CHAI Haokai

“…To address the problem of missed detection and slow detection speed in safety belt wearing test for electric aloft work, this paper proposed a method for detecting the wearing of safety belts based on EPSA-YOLOv5 algorithm. …”
Get full text

UAVAI-YOLO: dense small target detection algorithm based on UAV aerial images by HE Zhiqian, CAO Lijie

“…An improved UAVAI-YOLO model was proposed to address the problem of poor target detection in UAV aerial images. …”
Get full text

Enhanced YOLOv8-based pavement crack detection: A high-precision approach. by ZuXuan Zhang, HongLi Zhang, TongJia Zhang

“…At present, the repair of cracks is still implemented manually, which has the problems of low identification efficiency and high labor cost. …”
Get full text

AReal-time Detection Method of Vehicle Target Based on Improved YOLOv5s Algorithm by CHEN Xiufeng, WANG Chengxin, WU Yuechen, GU Kexin

“…To improve the detection rate of small target vehicles，an optimization of the YOLOv5s algorithm network structure was established，which added a small target detection layer and spliced the shallow feature map with the deep feature map in the detection. …”
Get full text

Surrounding Object Material Detection and Identification Method for Robots Based on Ultrasonic Echo Signals by Bo Zhu, Tao Geng, Gedong Jiang, Zheng Guan, Yang Li, Xialun Yun

Get full text

SAR ship target detection method based on CNN structure with wavelet and attention mechanism. by Shiqi Huang, Xuewen Pu, Xinke Zhan, Yucheng Zhang, Ziqi Dong, Jianshe Huang

“…Ship target detection in synthetic aperture radar (SAR) images is an important application field. …”
Get full text

The clinical significance of the features of the morphological study and immunohistochemical determination of pancytokeratin in the lymph nodes of the central zone in papillary thy... by D.  A. Galushko, H.  G. Asmaryan, N.  V. Melnikova, I.  A. Lazukina

Get full text

A Malware Detection Method Based on Genetic Algorithm Optimized CNN-SENet Network by Zheng Yang, Hua Zhu, Zhao Li, Gang Wang, Meng Su

“…With the popularization of smart terminals and the gradual increase of power grid informatization and digitization, the protection of power monitoring systems from various cybersecurity threads is a current scientific problem that needs to be solved urgently. To this end, this paper proposes a malware detection method based on genetic algorithm optimization of the CNN-SENet network, which firstly introduces the SENet attention mechanism into the convolutional neural network to enhance the spatial feature extraction capability of the model; then, the application programming interface (API) sequences corresponding to different software behaviors are processed by segmentation and de-duplication, which in turn leads to the sequence feature extraction through the CNN-SENet model; finally, genetic algorithm is used to optimize the hyperparameters of CNN-SENet network to reduce the computational overhead of CNN and to achieve the recognition and classification of different malware at the output layer. …”
Get full text

An efficient bearing fault detection strategy based on a hybrid machine learning technique by Khalid Alqunun, Mohammed Bachir Bechiri, Mohamed Naoui, Abderrahmane Khechekhouche, Ismail Marouani, Tawfik Guesmi, Badr M. Alshammari, Amer AlGhadhban, Abderrahim Allal

“…Abstract This study introduces an innovative method for addressing the bearing fault detection problem in rotating machinery. The proposed approach integrates multi-feature extraction, advanced feature selection, and state-of-the-art classification techniques using convolutional neural network (CNN) models. …”
Get full text