Academic Articles & Research Papers

Fundamentals of Computer Vision

Computer vision has widespread and growing application including robotics, autonomous vehicles, medical imaging and diagnosis, surveillance, video analysis, and even tracking for sports analysis. This book equips the reader with crucial mat...

2012 IEEE Conference on Computer Vision and Pattern Recognition

Color of Salmon Fillets By Computer Vision and Sensory Panel

Computer Vision and Natural Constraints

Computer vision, the automatic construction of scene descriptions from image input data, has just entered its second decade. Approaches have varied widely, especially in the amounts of symbolic, domain-dependent knowledge and inference that...

Computer vision vs. human vision

In object recognition (classification), it was known that the human brain processes visual information in semantic space mainly, that is, extracting the semantically meaningful features such as line-segments, boundaries, shape and so on. Bu...

Kernel Methods in Computer Vision

Over the last years, kernel methods have established themselves as powerful tools for computer vision researchers as well as for practitioners. In this tutorial, we give an introduction to kernel methods in computer vision from a geometric ...

Federated Learning in Computer Vision

Federated Learning (FL) has recently emerged as a novel machine learning paradigm allowing to preserve privacy and to account for the distributed nature of the learning process in many real-world settings. Computer vision tasks deal with hu...

Automated estimation of cementitious sorptivity via computer vision

Monitoring water uptake in cementitious systems is crucial to assess their durability against corrosion, salt attack, and freeze-thaw damage. However, gauging absorption currently relies on labor-intensive and infrequent weight measurements...

Learning techniques used in computer vision for food quality evaluation: a review

Computer Vision – ECCV 2024

Advanced Swine Management: Infrared Imaging for Precise Localization of Reproductive Organs in Livestock Monitoring

Traditional methods for predicting sow reproductive cycles are not only costly but also demand a larger workforce, exposing workers to respiratory toxins, repetitive stress injuries, and chronic pain. This occupational hazard can even lead ...

Cross-Correlation-Based Structural System Identification Using Unmanned Aerial Vehicles

Computer vision techniques have been employed to characterize dynamic properties of structures, as well as to capture structural motion for system identification purposes. All of these methods leverage image-processing techniques using a st...

Performance Benchmarking: Pre-trained Models and Custom Convolutional Neural Networks in Deep Learning

Recent advances in computer vision and deep learning, particularly Convolutional Neural Networks (CNNs), have significantly increased road safety. CNNs were used in this work to automatically detect and categorise traffic signs—a crucial ta...

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...

Multi‐object tracking using dominant sets

Multi‐object tracking is an interesting but challenging task in the field of computer vision. Most previous works based on data association techniques merely take into account the relationship between detection responses in a locally limite...

Real Time Eye Detector with Cascaded Convolutional Neural Networks

An accurate and efficient eye detector is essential for many computer vision applications. In this paper, we present an efficient method to evaluate the eye location from facial images. First, a group of candidate regions with regional extr...

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...

Repurposing a commercial artificial intelligence vision platform for automated surgical instrument identification: a proof-of-concept study

Abstract Background Retained surgical items are classified as never events but continue to occur, and the count meant to prevent them is often recorded as correct even when an item is retained. Computer vision could provide an independent c...

Risk factors of digital eye strain among computer users at Al-Baha University

Background: Digital eye strain (DES) affects an estimated 60 million people worldwide, with a higher prevalence among populations that are occupationally reliant on digital display devices. Aim: This study investigated risk factors of DES ...

A Complete System for Automated Semantic–Geometric Mapping of Corrosion in Industrial Environments

Corrosion, a naturally occurring process leading to the deterioration of metallic materials, demands diligent detection for quality control and the preservation of metal-based objects, especially within industrial contexts. Traditional tech...