Academic Articles & Research Papers

Natural Language Processing for Requirements Engineering

Natural Language Processing for Requirements Engineering (NLP4RE) is an area of research and development that seeks to apply natural language processing (NLP) techniques, tools, and resources to the requirements engineering (RE) process, to...

Documenting Computer Vision Datasets

In industrial computer vision, discretionary decisions surrounding the production of image training data remain widely undocumented. Recent research taking issue with such opacity has proposed standardized processes for dataset documentatio...

Cross-modal correlations in ensemble averaging across vision, audition, and touch.

Autonomous Driving Roadway Feature Interpretation Using Integrated Semantic Analysis and Domain Adaptation

Lane detection is fundamental to autonomous driving, yet remains challenging in complex environments with occlusions, ambiguous markings, and varied lighting. We introduce the Global Semantic Enhancement Network (GSENet), a groundbreaking f...

Perceptual organization in computer vision: a review and a proposal for a classificatory structure

The role of perceptual organization in computer vision systems is explored. This is done from four vantage points. A brief history of perceptual organization research in both humans and computer vision is offered. A classificatory structure...

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...

Key Technologies of Vehicle Active Safety System Based on Computer Vision

Due to the increase in the number of urban vehicles and the irregular driving behavior of drivers, urban accidents frequently occur, causing serious casualties and economic losses. Active vehicle safety systems can monitor vehicle status an...

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...

Calibration and Orientation of Cameras in Computer Vision

One of my greatest hates is the edited book with chapters from a number of different authors, some of which have evidently been written in haste against the final deadline, and most of which show marked divergence of content, opinion, notat...

Computer Vision Syndrome: Prevalence and Associated Risk Factors among Undergraduates in a Tertiary Institution in North western Nigeria

Background: Computers and other visual display devices have become essential in the present era and have led to a rise in computer-related health problems. Using computers in homes, universities and other institutions has increased output g...

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...

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 ...

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...

Enhanced Combined Techniques for Interval-Valued Intuitionistic Fuzzy Multiple-Attribute Group Decision-Making and Applications to Quality Evaluation of Large-Scale Multi-View 3D Reconstruction

With the widespread application of computer vision in many fields, quickly and accurately obtaining the three-dimensional information covered by the target object has become a concern in the field of vision research. Large scale multi view ...

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...

Data Efficient Vision Transformer Based Model for Brain Tumor Classification in MRI

Accurate detection of brain tumors at early stages is crucial for clinical diagnosis and treatment planning. Magnetic Resonance Imaging (MRI) is the most popular method due to its soft-tissue contrast and spatial resolution. However, manual...

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. This mo...

Visual Target P3b Amplitude Mediates the Relationship between Childhood Traumatic Experiences and Social Functioning in People at Clinical High Risk for Psychosis.

Deeply Exploiting Long-Term View Dependency for 3D Shape Recognition

Recognition of 3D shapes is a fundamental task in computer vision. In recent years, view-based deep learning has emerged as an effective approach for 3D shape recognition. Most existing view-based methods treat the views of an object as an ...

Potential of machine learning approaches for predicting mechanical properties of spruce wood in the transverse direction

Abstract To predict the mechanical properties of wood in the transverse direction, this study used machine learning to extract the anatomical features of wood from cross-sectional stereograms. Specimens with different orientations of the ra...