Academic Articles & Research Papers

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 ...

Per-Sample Multiple Kernel Approach for Visual Concept Learning

Learning visual concepts from images is an important yet challenging problem in computer vision and multimedia research areas. Multiple kernel learning (MKL) methods have shown great advantages in visual concept learning. As a visual concep...

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 ...

Deep Learning for Understanding Satellite Imagery: An Experimental Survey

Translating satellite imagery into maps requires intensive effort and time, especially leading to inaccurate maps of the affected regions during disaster and conflict. The combination of availability of recent datasets and advances in compu...

Monitoring pedestrian walking dynamics under environmental and policy influences in urban spaces

Abstract Understanding how environmental conditions and policy interventions jointly shape pedestrian mobility is essential for designing resilient, adaptive, and human-centered urban spaces. This study presents a computer-vision framework ...

Toward Automated Structural Design for Controlled Vibration Characteristics Using Topology Optimization and Computer Vision in Space Missions

This study explores the integration of computer vision with topology optimization for additive manufacturing, with a focus on maximizing eigenfrequency in a design domain. Utilizing custom-developed photogrammetry software, high-resolution ...

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 ...

Computer Vision and Pattern Recognition 2020

This special issue covers a wide range of topics from the area of Computer Vision, Pattern Recognition, and Machine Learning.This breadth of scope is reflected by the papers included in this special issue, which touch topics including geome...

The psychological impact of the Metaverse

Abstract The Metaverse is no revolution, but another step in the evolution of the internet. Today we can observe various 3D virtual worlds with different focuses and purposes, like meeting spaces, education, or classic gaming. Most of these...

Approximating Cognitive Representations Using Space.

Multimodal Phase-Space Dynamics Fusion for Robust Ischemia Screening: An Edge-AI Paradigm with SERF Magnetocardiography

Background: Myocardial ischemia (MI) is a major cause of morbidity and mortality worldwide and requires timely and reliable detection. Although Spin-Exchange Relaxation-Free (SERF) magnetocardiography (MCG) provides femtotesla-level sensiti...

Scale-Space Theory in Computer Vision

TRust Your GENerator (TRYGEN): Enhancing Out-of-Model Scope Detection

Recent research has drawn attention to the ambiguity surrounding the definition and learnability of Out-of-Distribution recognition. Although the original problem remains unsolved, the term “Out-of-Model Scope” detection offers a clearer pe...

Spatiotemporal patterns induced by four mechanisms in a tussock sedge model with discrete time and space variables

Abstract In this paper, we investigate the spatiotemporal patterns of a freshwater tussock sedge model with discrete time and space variables. We first analyze the kinetic system and show the parametric conditions for flip and Neimark–Sacke...

Scale-Space Theory in Computer Vision

Scale-Space Theories in Computer Vision

Improving Image Embeddings With Colour Features in Indoor Scene Geolocation

Embeddings remain the best way to represent image features, but do not always capture all latent information. This is still a problem in representation learning, and computer vision descriptors struggle with precision and accuracy. Improvin...

Inversion Analysis Method for Tunnel and Underground Space Engineering: A Short Review

With the rise of the fourth industrial revolution, traditional methods of analyzing investment have been transformed into intelligent methods under big data and the Internet of Things. This has created a new approach to solving practical en...

A computer vision for animal ecology

A central goal of animal ecology is to observe species in the natural world. The cost and challenge of data collection often limit the breadth and scope of ecological study. Ecologists often use image capture to bolster data collection in t...

Euclid Quick Data Release (Q1)

Strong gravitational lensing (SL) by galaxy clusters is a powerful probe of their inner mass distribution and a key test bed for cosmological models. However, the detection of SL events in wide-field surveys such as Euclid requires robust a...