Multi-Scale Residual Convolutional Neural Network with Hybrid Attention for Bearing Fault Detection by Yanping Zhu, Wenlong Chen, Sen Yan, Jianqiang Zhang, Chenyang Zhu, Fang Wang, Qi Chen

“…This paper proposes an advanced deep convolutional neural network model for motor bearing fault detection that was designed to overcome the limitations of traditional models in feature extraction, accuracy, and generalization under complex operating conditions. …”
Get full text

A Noninvasive System for the Automatic Detection of Gliomas Based on Hybrid Features and PSO-KSVM by Guoli Song, Zheng Huang, Yiwen Zhao, Xingang Zhao, Yunhui Liu, Min Bao, Jianda Han, Peng Li

“…However, it is a challenging task to detect the gliomas within the complex structure of the brain. …”
Get full text

High catalytic nickel-platinum nanozyme enhancing colorimetric detection of Salmonella Typhimurium in milk by Jie Zhu, Lingyue Xu, Junlin Zhang, Yuxin Wang, Hongyue Yu, Chuanchuan Hao, Guohui Cheng, Daofeng Liu, Minghui Chen

“…Meanwhile, the antibody employed in this NiPt NP-based NLISA exhibits exceptional capture efficacy, generating a stable immune complex with Salmonella Typhimurium. The NiPt NP-based NLISA demonstrates sensitivity, specificity, convenience, and cost-efficiency for the detection of Salmonella Typhimurium. …”
Get full text

FQDNet: A Fusion-Enhanced Quad-Head Network for RGB-Infrared Object Detection by Fangzhou Meng, Aoping Hong, Hongying Tang, Guanjun Tong

“…RGB-IR object detection provides a promising solution for complex scenarios, such as remote sensing and low-light environments, by leveraging the complementary strengths of visible and infrared modalities. …”
Get full text

Hierarchical Feature Fusion and Enhanced Attention Mechanism for Robust GAN-Generated Image Detection by Weinan Zhang, Sanshuai Cui, Qi Zhang, Biwei Chen, Hui Zeng, Qi Zhong

“…Meanwhile, the AEM enhances the network’s ability to capture subtle forgery traces by incorporating attention mechanisms and filtering techniques, significantly boosting the model’s efficiency in processing complex information. The experimental results demonstrate that the proposed method achieves significant improvements across all evaluation metrics. …”
Get full text

Enhancing Object Detection in Underground Mines: UCM-Net and Self-Supervised Pre-Training by Faguo Zhou, Junchao Zou, Rong Xue, Miao Yu, Xin Wang, Wenhui Xue, Shuyu Yao

“…However, limited computational resources and complex environmental conditions in mine shafts significantly impact the recognition and computational capabilities of detection models. …”
Get full text

Crystal structures of DCAF1-PROTAC-WDR5 ternary complexes provide insight into DCAF1 substrate specificity by Mark F. Mabanglo, Brian Wilson, Mahmoud Noureldin, Serah W. Kimani, Ahmed Mamai, Chiara Krausser, Héctor González-Álvarez, Smriti Srivastava, Mohammed Mohammed, Laurent Hoffer, Manuel Chan, Jamie Avrumutsoae, Alice Shi Ming Li, Taraneh Hajian, Sarah Tucker, Stuart Green, Magdalena Szewczyk, Dalia Barsyte-Lovejoy, Vijayaratnam Santhakumar, Suzanne Ackloo, Peter Loppnau, Yanjun Li, Almagul Seitova, Taira Kiyota, Jue George Wang, Gilbert G. Privé, Douglas A. Kuntz, Bhashant Patel, Vaibhavi Rathod, Anand Vala, Bhimsen Rout, Ahmed Aman, Gennady Poda, David Uehling, Jailall Ramnauth, Levon Halabelian, Richard Marcellus, Rima Al-awar, Masoud Vedadi

“…We report four DCAF1-based PROTACs with endogenous and exogenous WDR5 degradation effects and high-resolution crystal structures of the ternary complexes of DCAF1-PROTAC-WDR5. The structures reveal detailed insights into the interaction of DCAF1 with various WDR5-PROTACs, indicating a significant role of DCAF1 loops in providing needed surface plasticity, and reflecting the mechanism by which DCAF1 functions as a substrate receptor for E3 ligases with diverse sets of substrates.…”
Get full text

DAU-YOLO: A Lightweight and Effective Method for Small Object Detection in UAV Images by Zeyu Wan, Yizhou Lan, Zhuodong Xu, Ke Shang, Feizhou Zhang

“…However, drone images typically exhibit challenges such as small object sizes, dense distributions, and high levels of overlap. Traditional object detection networks struggle to achieve the required accuracy and efficiency under these conditions. …”
Get full text

Improved Asphalt Pavement Crack Detection Model Based on Shuffle Attention and Feature Fusion by Tursun Mamat, Abdukeram Dolkun, Runchang He, Yonghui Zhang, Zulipapar Nigat, Hanchen Du

“…Pavement distress is one of the most serious and prevalent diseases in pavement road detection. However, traditional methods for crack detection often suffer from low efficiency and limited accuracy, necessitating improvements in the accuracy of existing crack detection algorithms. …”
Get full text

A hybrid approach using support vector machine rule-based system: detecting cyber threats in internet of things by M. Wasim Abbas Ashraf, Arvind R. Singh, A. Pandian, Rajkumar Singh Rathore, Mohit Bajaj, Ievgen Zaitsev

“…Complex threats often go undetected by conventional security measures, requiring more sophisticated, adaptive detection methods. …”
Get full text

Research on Ship Heave Motion Compensation Control Under Complex Sea State Environment Based on Improved Reinforcement Learning by ZHANG Qin, ZHOU Jingyi, WANG Xingyue, HU Xiong

“…The TD3 algorithm approximates the value function and policy by harnessing deep neural networks, equipping it to tackle complex and nonlinear sea condition challenges. Aligned with the uncertainty and complexity entailed by the maritime milieu, this study specifically fine‒tunes the output layer of the Actor network by amplifying the amplitude of the TanH function. …”
Get full text

Integrated neural network framework for multi-object detection and recognition using UAV imagery by Mohammed Alshehri, Tingting Xue, Tingting Xue, Ghulam Mujtaba, Yahya AlQahtani, Nouf Abdullah Almujally, Ahmad Jalal, Ahmad Jalal, Hui Liu, Hui Liu, Hui Liu

“…The proposed framwork integrates multiple advanced modules: RetinexNet for preprocessing, segmentation using HRNet to preserve high-resolution semantic information, and vehicle detection using the YOLOv11 framework. Deep SORT is employed for efficient vehicle tracking, while CSRNet facilitates high-density vehicle counting. …”
Get full text

Detection of Surface Defects in Steel Based on Dual-Backbone Network: MBDNet-Attention-YOLO by Xinyu Wang, Shuhui Ma, Shiting Wu, Zhaoye Li, Jinrong Cao, Peiquan Xu

“…Automated surface defect detection in steel manufacturing is pivotal for ensuring product quality, yet it remains an open challenge owing to the extreme heterogeneity of defect morphologies—ranging from hairline cracks and microscopic pores to elongated scratches and shallow dents. …”
Get full text

DVAEGMM: Dual Variational Autoencoder With Gaussian Mixture Model for Anomaly Detection on Attributed Networks by Wasim Khan, Mohammad Haroon, Ahmad Neyaz Khan, Mohammad Kamrul Hasan, Asif Khan, Umi Asma Mokhtar, Shayla Islam

“…In this paper, we propose a new framework called DVAEGMM to detect anomalies on attributed networks. First, our framework utilizes a dual variational autoencoder for capturing the complex cross-modality relationships between node attributes and network structure, like vanilla autoencoders, but it also considers the potential data distribution and makes use of a generative adversarial network (GAN) for an adversarial regularization approach. …”
Get full text

Method of Calculation of Integrated Performance Indicators of Defense Industry Organizations by S. E. Eroshin

“…The purpose of the study is to develop a parametric monitoring system for defense industry enterprises, optimizing on the principle of minimum sufficiency a set of key indicators of the activities of organizations and increasing the efficiency of management of research institutes, design bureaus, industrial and service enterprises of the military-industrial complex.Materials and methods. …”
Get full text

Network-Based Bag-of-Words Model for Text Classification by Dongyang Yan, Keping Li, Shuang Gu, Liu Yang

Get full text

Dynahead-YOLO-Otsu: an efficient DCNN-based landslide semantic segmentation method using remote sensing images by Zheng Han, Bangjie Fu, Zhenxiong Fang, Yange Li, Jiaying Li, Nan Jiang, Guangqi Chen

“…This is achieved by locating potential landslide regions in advance using the ODD-based Dynahead-YOLO model, which enhances the capacity for detecting landslides with variable proportions and complex background in the images. …”
Get full text

LitePipeNet: Research on a Lightweight and Efficient Segmentation Model for UAV Pipeline Inspection in Mining Areas by Huang Yong, Xiao Shengwang, Xia Xing, Huang Qiu

“…In response to the challenges of UAV-based pipeline inspection in mining areas—including difficulties in small object detection, limited adaptability to complex environments, and constraints on efficient edge deployment—this paper proposes LitePipeNet, a lightweight segmentation model tailored for edge computing. …”
Get full text

Efficient Stereo Visual Odometry on FPGA Featuring On-Chip Map Management and Pipelined Descriptor-Based Block Matching by Yuki Ichikawa, Kazushi Kawamura, Masato Motomura, Thiem van Chu

“…These irregular patterns arise from the dynamic and non-uniform nature of feature detection, stereo matching, and map management, which vary significantly with scene complexity and camera movement. …”
Get full text

Prototyping a graph-based approach for efficient vehicle tracking in a cluster controlled CCTV surveillance systems by Apurva NARAYAN, Charumathi PARIVALLAL, Olirva MAHESWARAN, Sarath CHANDRAN KALATHILPARAMBIL RAMACHANDRAN

“…Addressing the growing challenges of vehicle density and traffic complexity, the system employs state-of-the-art deep learning techniques for real-time vehicle detection, tracking, and route analysis. …”
Get full text