Academic Articles & Research Papers

SCM: A Searched Convolutional Metaformer for SAR Ship Classification

Ship classification technology using synthetic aperture radar (SAR) has become a research hotspot. Many deep-learning-based methods have been proposed with handcrafted models or using transplanted computer vision networks. However, most of ...

Problems In Indoor Mapping and Modelling

Research in support of indoor mapping and modelling (IMM) has been active for over thirty years. This research has come in the form of As-Built surveys, Data structuring, Visualisation techniques, Navigation models and so forth. Much of thi...

Computer Vision and Image Processing: A Practical Approach Using CVIPTools

From the Publisher: True computer imaging for engineers! Digital signal processing has long been the domain of electrical engineers, while the manipulation of image data has been handled by computer scientists. The convergence of these...

Vision Transformers in medical computer vision—A contemplative retrospection

Computer Vision Techniques in Manufacturing

Computer vision techniques have played an important role in promoting the informatization, digitization and intelligence of industrial manufacturing systems. Considering the rapid development of computer vision techniques, we present a comp...

Robust Techniques for Computer Vision

ysis 1995, pages 191--208. AddisonWesley Longman, 1996. [116] R. H. Zamar. Robust estimation in the errors-in-variables model. Biometrika, 76:149-- 160, 1989. [117] Z. Zhang. Determining the epipolar geometry and its uncertainty: A review. ...

Structured Learning and Prediction in Computer Vision

Powerful statistical models that can be learned efficiently from large amounts of data are currently revolutionizing computer vision. These models possess a rich internal structure reflecting task-specific relations and constraints. Structu...

Robust Parameter Estimation in Computer Vision

Estimation techniques in computer vision applications must estimate accurate model parameters despite small-scale noise in the data, occasional large-scale measurement errors (outliers), and measurements from multiple populations in the sam...

Machine Vision and Canny Edge Detector–Based Printing Image Detection and Recognition Model

Traditional image detection and recognition models face issues such as high miss detection rates, low classification accuracy, and poor real-time performance when dealing with complex printing images, including defects and flaws. To address...

Video Processing Using Deep Learning Techniques: A Systematic Literature Review

Studies show lots of advanced research on various data types such as image, speech, and text using deep learning techniques, but nowadays, research on video processing is also an emerging field of computer vision. Several surveys are presen...

Strawberry plant wetness detection using computer vision and deep learning

Botrytis fruit rot and anthracnose are fungal diseases of strawberry. These diseases are a significant contributor to yield losses, requiring farmers to use fungicides frequently to prevent them. The proliferation of botrytis and anthracnos...

The Validity and Reliability of the My Jump Lab App for the Measurement of Vertical Jump Performance Using Artificial Intelligence

The countermovement jump (CMJ) is a widely used test to assess lower body neuromuscular performance. This study aims to analyze the validity and reliability of an iOS application using artificial intelligence to measure CMJ height, force, v...

Research on Landscape Perception and Visual Attributes Based on Social Media Data—A Case Study on Wuhan University

With the rapid rise of social media, the photo-taking behavior of tourists and their uploaded photos provide a new perspective to explore landscape visual characters. In this study, we provide methodological advancements for assessing lands...

A Video Frame Prediction Method Based on Latent-Space Autoregressive Modeling

Video prediction is a fundamental task in computer vision with broad applications in intelligent robotics, autonomous driving, and related fields. However, existing methods often struggle to simultaneously model long-term temporal dependenc...

Florence: A New Foundation Model for Computer Vision

Automated visual understanding of our diverse and open world demands computer vision models to generalize well with minimal customization for specific tasks, similar to human vision. Computer vision foundation models, which are trained on d...

Domain Adaptation in Computer Vision Applications

Remote sensing image road network detection based on channel attention mechanism

Extracting and detecting road network consistency from high-resolution remote sensing images has been a hot and difficult problem in the computer vision. Although it has made significant progress, there is still a phenomenon of high trainin...

Approaches to Improve the Quality of Person Re-Identification for Practical Use

The idea of the person re-identification (Re-ID) task is to find the person depicted in the query image among other images obtained from different cameras. Algorithms solving this task have important practical applications, such as illegal ...

Unmanned Aerial Vehicle-Based Structural Health Monitoring and Computer Vision-Aided Procedure for Seismic Safety Measures of Linear Infrastructures

Computer vision in the structural health monitoring (SHM) field has become popular, especially for processing unmanned aerial vehicle (UAV) data, but still has limitations both in experimental testing and in practical applications. Prior wo...

Evaluation of Modified FGSM-Based Data Augmentation Method for Convolutional Neural Network-Based Image Classification

Computer vision applications demand a significant amount of data for effective training and inference in many computer vision tasks. However, data insufficiency situations usually happen due to multiple reasons, resulting in computational m...