Academic Articles & Research Papers

A hybrid CNN-BiLSTM network with additive attention for automated four-stage classification of Alzheimer's disease from brain MRI.

Research progress and trends of deep learning based wireless communication receiving method

With the continues expansion of the application boundary for wireless communications, the application environment of wireless communications is becoming increasingly complex and diverse, which faces negative impacts such as radio frequency ...

UPANets: Learning from the Universal Pixel Attention Neworks

With the successful development in computer vision, building a deep convolutional neural network (CNNs) has been mainstream, considering the character of shared parameters in a convolutional layer. Stacking convolutional layers into a deep ...

Geo-Temporal Selective Approach for Dynamic Depth Estimation in Outdoor Object Detection and Distance Measurement

Accurate depth information is crucial for various computer vision applications such as augmented reality, 3D modeling, and autonomous vehicles. Recent advancements have significantly improved both supervised and self-supervised methods for ...

Unconstrained Bilingual Scene Text Reading Using Octave as a Feature Extractor

Reading text and unified text detection and recognition from natural images are the most challenging applications in computer vision and document analysis. Previously proposed end-to-end scene text reading methods do not consider the freque...

Improved U-Net Model for Road Crack Detection Based on Residual and Attention Mechanism

Road cracks are an important part of road safety detection，and with the development of deep learning and computer vision，methods for extracting crack information in road images using deep learning methods are maturing.Existing deep learning...

TransCat: a hybrid CNN-transformer network with KAN for medical image segmentation

Medical image segmentation is a fundamental task in computer vision and plays an important role in clinical diagnosis and treatment planning. Existing methods are mainly built on either convolutional neural networks (CNNs) or Transformer-ba...

Lightweight Road Image Segmentation Algorithm Based on Multi-Scale Feature Fusion for Blind Guiding Scenarios

Image segmentation is a crucial technology for environmental perception, and it is widely used in various scenarios such as autonomous driving and virtual reality. With the rapid development of technology, computer vision-based blind guidin...

Computer Vision Meets Educational Robotics

Educational robotics has gained a lot of attention in the past few years in K-12 education. Prior studies have shown enough shreds of evidence and highlight the benefits of educational robotics as being effective in providing impactful lear...

A coarse to fine network for fast and accurate object detection in high‐resolution images

Abstract Because of the popularisation of high‐resolution images, detecting objects in these images quickly and accurately has attracted increasing attention in recent studies. Current convolutional neural networks (CNN)‐based detection met...

Performance Analysis of the SIFT Operator for Automatic Feature Extraction and Matching in Photogrammetric Applications

In the photogrammetry field, interest in region detectors, which are widely used in Computer Vision, is quickly increasing due to the availability of new techniques. Images acquired by Mobile Mapping Technology, Oblique Photogrammetric Came...

AN IMPROVED MASK R-CNN: EXTRACTION OF DOOR AND WINDOW INSTANCES ON VILLAGE BUILDING FAÇADE IMAGES

Rapid access to the basic structure of village buildings is conducive to the investigation of the load-bearing bodies of village houses and provides data support for disaster assessment and post-disaster rescue and reconstruction. The devel...

TSER: A Two-Stage Character Segmentation Network With Two-Stream Attention and Edge Refinement

Segmenting characters in an image is a classic yet challenging task in computer vision. Correctly determining boundaries of adhesive characters with various scales and shapes is essential for character segmentation, especially for separatin...

A review of computer vision–based structural health monitoring at local and global levels

Structural health monitoring at local and global levels using computer vision technologies has gained much attention in the structural health monitoring community in research and practice. Due to the computer vision technology application a...

Computer Vision in Healthcare Applications

The research of computer vision, imaging processing and pattern recognition has made substantial progress during the past several decades.Also, medical imaging has attracted increasing attention in recent years due to its vital component in...

Assessing Wireless Sensing Potential With Large Intelligent Surfaces

Sensing capability is one of the most highlighted new feature of future 6G wireless networks. This paper addresses the sensing potential of Large Intelligent Surfaces (LIS) in an exemplary Industry 4.0 scenario. Besides the attention receiv...

Soft–Hard Attention U-Net Model and Benchmark Dataset for Multiscale Image Shadow Removal

Effective shadow removal is pivotal in enhancing visual image quality in applications such as computer vision and digital photography. During the last decades physics-based and machine learning methodologies have been proposed; however, mos...

Adversarial Attack on Object Detection via Object Feature-Wise Attention and Perturbation Extraction

Deep neural networks are commonly used in computer vision tasks, but they are vulnerable to adversarial samples, resulting in poor recognition accuracy. Although traditional algorithms that craft adversarial samples have been effective in a...

UAC-Net: a unified multi-task network with aggregated contextual attention and cross-layer fusion for brain tumor segmentation and classification.

Fuzzy Comprehensive Evaluation Model of Project Investment Risk Based on Computer Vision Technology

With the development of the economy and real-time embedded systems and the progress of science and technology, people’s economic income forms have undergone tremendous changes, and the concept of financial management has become clearer in p...