Academic Articles & Research Papers

Artificial Intelligence and Digital Pathology: Challenges and Opportunities

In light of the recent success of artificial intelligence (AI) in computer vision applications, many researchers and physicians expect that AI would be able to assist in many tasks in digital pathology. Although opportunities are both manif...

Robotic Template Library

Robotic Template Library (RTL) is a set of tools for dealing with geometry and point cloud processing, especially in robotic applications. The software package covers basic objects such as vectors, line segments, quaternions, rigid transfor...

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 ...

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...

PAMPAS: real-valued graphical models for computer vision

Probabilistic models have been adopted for many computer vision applications, however inference in high-dimensional spaces remains problematic. As the state-space of a model grows, the dependencies between the dimensions lead to an exponent...

Computer Vision Applications in Intelligent Transportation Systems: A Survey

As technology continues to develop, computer vision (CV) applications are becoming increasingly widespread in the intelligent transportation systems (ITS) context. These applications are developed to improve the efficiency of transportation...

OpenCV for Computer Vision Applications

OpenCV is a powerful, open-source toolkit designed for handling real-time computer vision challenges and advanced image processing tasks. It enables automated systems to interpret images and videos effectively. This paper explores the capab...

Computer vision applications in construction: Current state, opportunities & challenges

Computer vision applications in offsite construction

Computer vision applications in vascular surgery: From preoperative mapping to intraoperative flow assessment

Artificial intelligence (AI) and computer vision (CV) are increasingly applied in vascular surgery for preoperative mapping and intraoperative flow/perfusion assessment, with potential to enhance safety and efficiency. However, the extent o...

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...

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

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...

OpenCV 2 Computer Vision Application Programming Cookbook

This is a cookbook that shows results obtained on real images with detailed explanations and the relevant screenshots. The recipes contain code accompanied with suitable explanations that will facilitate your learning. If you are a novice C...

Survey on Videos Data Augmentation for Deep Learning Models

In most Computer Vision applications, Deep Learning models achieve state-of-the-art performances. One drawback of Deep Learning is the large amount of data needed to train the models. Unfortunately, in many applications, data are difficult ...

Color in Computer Vision

While the field of computer vision drives many of today’s digital technologies and communication networks, the topic of color has emerged only recently in most computer vision applications. One of the most extensive works to date on color i...

Computer Vision: A First Course

Computer vision is a new discipline recently developed from image processing, which is able to take raw images, and, after suitable processing, derive information from them automatically. Computer vision applications are legion in the areas...

Cross-Attention Joint Denoising and Semantic Segmentation for Robust Image Analysis

Semantic segmentation assigns class labels at the pixel level, forming a key part of various computer vision applications, including autonomous driving, medical imaging, and robotics. However, segmentation accuracy often drops significantly...