Academic Articles & Research Papers

Adversarial Attack on Object Detection via Object Feature-Wise Attention and Perturbation Extraction

Deep neural networks are commonly used in computer vision tasks, but they are vulnerable to adversarial samples, resulting in poor recognition accuracy. Although traditional algorithms that craft adversarial samples have been effective in a...

Autonomous Robotic Platform for Precision Viticulture: Integrated Mobility, Multimodal Sensing, and AI-Based Leaf Sampling

Viticulture is facing growing economic and environmental pressures that demand a transition toward intelligent and autonomous crop management systems. Phytopathologies remain one of the most critical threats, causing substantial yield losse...

Towards automated metaphase cell detection using foundation models: A SAM and DINO-based approach

Karyotyping is a widely used laboratory technique to detect abnormalities in chromosomes. Karyotyping consists of many steps, including collecting samples, cell culturing and metaphase cell detection. Cytogeneticists examine all the images ...

Experimental study of a novel contact-based pose detection approach for digital twin-driven high-precision micro assembly

This study presents a comprehensive study of a novel Contact-Based Pose Estimation Method (CBPEM) for enhancing precision in robotic assembly processes within digital twin frameworks. Conventional pose detection methods, such as laser and c...

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...

Head Pose Estimation in Computer Vision: A Survey

The capacity to estimate the head pose of another person is a common human ability that presents a unique challenge for computer vision systems. Compared to face detection and recognition, which have been the primary foci of face-related vi...

Review of Weed Detection Methods Based on Computer Vision

Weeds are one of the most important factors affecting agricultural production. The waste and pollution of farmland ecological environment caused by full-coverage chemical herbicide spraying are becoming increasingly evident. With the contin...

A survey of public datasets for computer vision tasks in precision agriculture

Computer vision technologies have attracted significant interest in precision agriculture in recent years. At the core of robotics and artificial intelligence, computer vision enables various tasks from planting to harvesting in the crop pr...

HalluciGuard-eye: knowledge graph-enhanced retrieval-augmented generation for hallucination detection and mitigation in ophthalmic multimodal large language models.

Mammography datasets and artificial intelligence for breast cancer detection: challenges, bias, and future directions.

A Self-Adaptive Traffic Signal System Integrating Real-Time Vehicle Detection and License Plate Recognition for Enhanced Traffic Management

Traffic management systems play a crucial role in smart cities, especially because increasing urban populations lead to higher traffic volumes on roads. This results in increased congestion at intersections, causing delays and traffic viola...

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...

Computer vision algorithms and hardware implementations: A survey

The field of computer vision is experiencing a great-leap-forward development today. This paper aims at providing a comprehensive survey of the recent progress on computer vision algorithms and their corresponding hardware implementations. ...

Detection and Control Framework for Unpiloted Ground Support Equipment within the Aircraft Stand

The rapid advancement in Unpiloted Robotic Vehicle technology has significantly influenced ground support operations at airports, marking a critical shift towards future development. This study presents a novel Unpiloted Ground Support Equi...

Deep-Learning based Melanoma Detection using Cloud Approach

The aim of computer vision techniquesand deep learning in the era of digitalization is to derive valuable insights from them and generate novel understanding. This makes it possible to employ imaging to quickly diagnose and treat a variety ...

A lightweight optimization framework for real-time pedestrian detection in dense and occluded scenes

Pedestrian detection is one of the most widely applied tasks in industrial computer vision. It encapsulates three core challenges of object detection: detecting small objects, handling heavy occlusion, and balancing speed and accuracy for d...

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...

An Improved Dense CNN Architecture for Deepfake Image Detection

Recent advancements in computer vision processing need potent tools to create realistic deepfakes. A generative adversarial network (GAN) can fake the captured media streams, such as images, audio, and video, and make them visually fit othe...

Video-Based Deep Learning Approach for 3D Human Movement Analysis in Institutional Hallways: A Smart Hallway

New artificial intelligence- (AI) based marker-less motion capture models provide a basis for quantitative movement analysis within healthcare and eldercare institutions, increasing clinician access to quantitative movement data and improvi...