Academic Articles & Research Papers

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...

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...

Automatic building detection and land use classification in urban areas using multispectral high-spatial resolution imagery and LiDAR data

Urban areas areimportant environments, accounting for approximately half the population of theworld. Cities attract residents partly because they offer ample opportunitiesfor development, which often results in urban sprawl and its complex ...

A Deep Learning-Driven Computer Vision and Web-Based Monitoring System for Automated Nutrient Management in Soilless Agriculture

Sustainable food production increasingly relies on intelligent automation technologies that optimize resource usage while maintaining crop health. This study presents a deep learning-driven computer vision and web based monitoring system de...

Spatially Aware Fusion in 3D Convolutional Autoencoders for Video Anomaly Detection

Surveillance videos are crucial for crime prevention and public safety, yet the challenge of defining abnormal events hinders their effectiveness, limiting the applicability of supervised methods. This paper introduces an unsupervised end-t...

Computer vision uncovers predictors of physical urban change

Which neighborhoods experience physical improvements? In this paper, we introduce a computer vision method to measure changes in the physical appearances of neighborhoods from time-series street-level imagery. We connect changes in the phys...

Adversarial robustness of deep learning-based thyroid nodule segmentation in ultrasound.

Evaluating Adversarial Robustness of No-Reference Image and Video Quality Assessment Models with Frequency-Masked Gradient Orthogonalization Adversarial Attack

Neural-network-based models have made considerable progress in many computer vision areas over recent years. However, many works have exposed their vulnerability to malicious input data manipulation—that is, to adversarial attacks. Although...

Convolutional-de-convolutional neural networks for recognition of surgical workflow

Computer-assisted surgery (CAS) has occupied an important position in modern surgery, further stimulating the progress of methodology and technology. In recent years, a large number of computer vision-based methods have been widely used in ...

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...

A Taxonomy of Deep Convolutional Neural Nets for Computer Vision

Traditional architectures for solving computer vision problems and the degree of success they enjoyed have been heavily reliant on hand-crafted features. However, of late, deep learning techniques have offered a compelling alternative -- th...

Adversarial domain adaptation for false-positive reduction in hospital-to-robotic echocardiographic screening under limited target-domain data.

DSpix2pix: A New Dual-Style Controlled Reconstruction Network for Remote Sensing Image Super-Resolution

Super-resolution reconstruction is a critical task in remote sensing image classification, and generative adversarial networks (GANs) have emerged as a dominant approach in this field. Traditional generative networks often produce low-quali...

Computer Perceptual Organization in Computer Vision

This book describes the design of a complete, flexible system for perceptual organization in computer vision using graph theoretic techniques, voting methods, and an extension of the Bayesian networks called perceptual inference networks (P...

Artificial Intelligence-Based Computer Vision Feedback to Improve Clinical Performance in Surgical Technology Education.

Assessment of the possibility of machine learning for electronic equipment quality prediction

The major algorithms and methods of machine learning are considered. A possibility of machine learning and neural network using for electronic equipment quality prediction is assessed. The paper provides examples of the successful applicati...

Kinematics of Negative Headshake in Seven Sign Languages.

Backhand-Approach-Based American Sign Language Words Recognition Using Spatial-Temporal Body Parts and Hand Relationship Patterns

Most of the existing methods focus mainly on the extraction of shape-based, rotation-based, and motion-based features, usually neglecting the relationship between hands and body parts, which can provide significant information to address th...

Generative Adversarial Networks in Computer Vision

Generative adversarial networks (GANs) have been extensively studied in the past few years. Arguably their most significant impact has been in the area of computer vision where great advances have been made in challenges such as plausible 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...