Academic Articles & Research Papers

The Intelligent Ecosystem: How we are Architecting the Future of Environmental Services with AI

As the global economy confronts the dual imperatives of ecological preservation and technological advancement, we at Veolia, are executing a comprehensive strategy that places Artificial Intelligence (AI) at the core of our operations and f...

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...

Image decomposition using a second-order variational model and wavelet shrinkage

The paper is devoted to the new model for image decomposition, that splits an image $f$ into three components $u+v+\omega$, with $u$ a piecewise-smooth or the ``cartoon'' component, $v$ a texture component and $\omega$ the noise part in var...

A comprehensive analytical assessment of dino-based architectures for sustainable automated potato inspection in the Al Kharj Region

Abstract Self-supervised learning (SSL) has emerged as a pivotal paradigm in computer vision, particularly for applications where labeled data are limited, costly, or labor-intensive to obtain. This paradigm is especially relevant to sustai...

Automated Cell Foreground–Background Segmentation with Phase-Contrast Microscopy Images: An Alternative to Machine Learning Segmentation Methods with Small-Scale Data

Cell segmentation is a critical step for image-based experimental analysis. Existing cell segmentation methods are neither entirely automated nor perform well under basic laboratory microscopy. This study proposes an efficient and automated...

SAIN:structure-aware image inpainting for large missing areas

Abstract Image inpainting is crucial for restoring missing or corrupted regions in images, with diverse applications in computer vision and digital content creation. Existing deep learning-based methods, however, often struggle with large o...

Lightweight Two-Layer Control Architecture for Human-Following Robot

(1) Background: Human detection and tracking are critical tasks for assistive autonomous robots, particularly in ensuring safe and efficient human–robot interaction in indoor environments. The increasing need for personal assistance among t...

SCM: A Searched Convolutional Metaformer for SAR Ship Classification

Ship classification technology using synthetic aperture radar (SAR) has become a research hotspot. Many deep-learning-based methods have been proposed with handcrafted models or using transplanted computer vision networks. However, most of ...

A Wilson–Cowan reservoir computer for interpretable spatiotemporal vision

Abstract We present a Wilson–Cowan reservoir computer (WC–RC) that treats a retinotopic excitatory–inhibitory neural field as a structured reservoir. Travelling waves and bounded oscillations provide an interpretable spatiotemporal basis, w...

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 ...

Machine Vision and Canny Edge Detector–Based Printing Image Detection and Recognition Model

Traditional image detection and recognition models face issues such as high miss detection rates, low classification accuracy, and poor real-time performance when dealing with complex printing images, including defects and flaws. To address...

Real-Time Fire Detection From Video Surveillance Cameras: Where Are We Now?

Automatic fire detection in video surveillance is a critical capability for safeguarding industrial sites, public infrastructures, and natural environments. Although recent advances in deep learning have substantially improved early fire de...

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...

The Validity and Reliability of the My Jump Lab App for the Measurement of Vertical Jump Performance Using Artificial Intelligence

The countermovement jump (CMJ) is a widely used test to assess lower body neuromuscular performance. This study aims to analyze the validity and reliability of an iOS application using artificial intelligence to measure CMJ height, force, v...

A Video Frame Prediction Method Based on Latent-Space Autoregressive Modeling

Video prediction is a fundamental task in computer vision with broad applications in intelligent robotics, autonomous driving, and related fields. However, existing methods often struggle to simultaneously model long-term temporal dependenc...

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...

The moderator effect of the family business protocol on the financial performance of born globals firms: A trajectories analysis.

Remote sensing image road network detection based on channel attention mechanism

Extracting and detecting road network consistency from high-resolution remote sensing images has been a hot and difficult problem in the computer vision. Although it has made significant progress, there is still a phenomenon of high trainin...

Feature Rescaling and Fusion for Tiny Object Detection

Recent years have witnessed rapid developments on computer vision, however, there are still challenges in detecting tiny objects in a large-scale background. The tiny objects knowledge become sparse and weak due to their tiny size, which ma...