Concrete crack detection using lightweight attention feature fusion single shot multibox detector

Joint-attention feature fusion network and dual-adaptive NMS for object detection

(2022) Wentao Ma et al.   KNOWLEDGE-BASED SYSTEMS

Automatic Detection of Cracks on Concrete Surfaces in the Presence of Shadows

(2022) Paulius Palevičius et al.   SENSORS

Correlation filters with adaptive convolution response fusion for object tracking

(2021) Lanlan Yang et al.   KNOWLEDGE-BASED SYSTEMS

Automatic Fetal Ultrasound Standard Plane Recognition Based on Deep Learning and IIoT

(2021) Bin Pu et al.   IEEE Transactions on Industrial Informatics

An Overview of Challenges Associated with Automatic Detection of Concrete Cracks in the Presence of Shadows

(2021) Mayur Pal et al.   Applied Sciences-Basel

BERT-Based Deep Spatial-Temporal Network for Taxi Demand Prediction

(2021) Dun Cao et al.   IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS

Increasing the robustness of material-specific deep learning models for crack detection across different materials

(2020) Mohamad Alipour et al.   ENGINEERING STRUCTURES

Citywide Traffic Flow Prediction Based on Multiple Gated Spatio-temporal Convolutional Neural Networks

(2020) Cen Chen et al.   ACM Transactions on Knowledge Discovery from Data

Multi-attention guided feature fusion network for salient object detection

(2020) Anni Li et al.   NEUROCOMPUTING

Hierarchical spatial-aware Siamese network for thermal infrared object tracking

(2018) Xin Li et al.   KNOWLEDGE-BASED SYSTEMS

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

(2017) Shaoqing Ren et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

A noise robust method based on completed local binary patterns for hot-rolled steel strip surface defects

(2013) Kechen Song et al.   APPLIED SURFACE SCIENCE

Selective Search for Object Recognition

(2013) J. R. R. Uijlings et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION

The Pascal Visual Object Classes (VOC) Challenge

(2009) Mark Everingham et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION