Academic Articles & Research Papers

Multi-Camera Machine Vision for Detecting and Analyzing Vehicle–Pedestrian Conflicts at Signalized Intersections: Deep Neural-Based Pose Estimation Algorithms

Over the past decade, researchers have advanced traffic monitoring using surveillance cameras, unmanned aerial vehicles (UAVs), loop detectors, LiDAR, microwave sensors, and sensor fusion. These technologies effectively detect and track veh...

Mobile system for road sign detection and recognition with template matching

This paper explores the effective approach to road sign detection and recognition based on mobile devices. Detecting and recognising road signs is a challenging matter because of different shapes, complex background and irregular sign illum...

Unipolar Barrier Near-Infrared 2D Photodetectors for 3D Image Sensors.

Melanoma Lesion Detection and Segmentation Using YOLOv4-DarkNet and Active Contour

Melanoma is the skin cancer caused by the ultraviolet radiation from the Sun and has only 15-20% of survival rate. Late diagnosis of melanoma leads to the severe malignancy of disease, and metastasis expands to the other body organs i.e. li...

Attack-Aware Deepfake Detection Under Counter-Forensic Manipulations

The rapid proliferation of AI-generated and manipulated visual content requires forensic detectors that remain reliable after routine processing and deliberate counter-forensic modification. This paper presents an attack-aware deepfake dete...

Computer vision vs. human vision

In object recognition (classification), it was known that the human brain processes visual information in semantic space mainly, that is, extracting the semantically meaningful features such as line-segments, boundaries, shape and so on. Bu...

Real Time Eye Detector with Cascaded Convolutional Neural Networks

An accurate and efficient eye detector is essential for many computer vision applications. In this paper, we present an efficient method to evaluate the eye location from facial images. First, a group of candidate regions with regional extr...

Performance Analysis of the SIFT Operator for Automatic Feature Extraction and Matching in Photogrammetric Applications

In the photogrammetry field, interest in region detectors, which are widely used in Computer Vision, is quickly increasing due to the availability of new techniques. Images acquired by Mobile Mapping Technology, Oblique Photogrammetric Came...

Effectual pre-processing with quantization error elimination in pose detector with the aid of image-guided progressive graph convolution network (IGP-GCN) for multi-person pose estimation

Multi-person pose estimation (MPE) remains a significant and intricate issue in computer vision. This is considered the human skeleton joint identification issue and resolved by the joint heat map regression network lately. Learning robust ...

Computer vision for computer games

The appeal of computer games may be enhanced by vision-based user inputs. The high speed and low cost requirements for near-term, mass-market game applications make system design challenging. The response time of the vision interface should...

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...

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...

Object detection in crowded scenes via joint prediction

Detecting highly-overlapped objects in crowded scenes remains a challenging problem, especially for one-stage detector. In this paper, we extricate YOLOv4 from the dilemma in a crowd by fine-tuning its detection scheme, named YOLO-CS. Speci...

Learning Feature Fusion in Deep Learning-Based Object Detector

Object detection in real images is a challenging problem in computer vision. Despite several advancements in detection and recognition techniques, robust and accurate localization of interesting objects in images from real-life scenarios re...

AriAplBud: An Aerial Multi-Growth Stage Apple Flower Bud Dataset for Agricultural Object Detection Benchmarking

As one of the most important topics in contemporary computer vision research, object detection has received wide attention from the precision agriculture community for diverse applications. While state-of-the-art object detection frameworks...

Computer Vision Metrics

Computer Vision Metrics provides an extensive survey and analysis of over 100 current and historical feature description and machine vision methods, with a detailed taxonomy for local, regional and global features. This book provides necess...

Secured Perimeter with Electromagnetic Detection and Tracking with Drone Embedded and Static Cameras

Perimeter detection systems detect intruders penetrating protected areas, but modern solutions require the combination of smart detectors, information networks and controlling software to reduce false alarms and extend detection range. The ...

Vision-Based Novelty Detection Using Deep Features and Evolved Novelty Filters for Specific Robotic Exploration and Inspection Tasks

One of the essential abilities in animals is to detect novelties within their environment. From the computational point of view, novelty detection consists of finding data that are different in some aspect to the known data. In robotics, re...

Intrusion Detection with Neural Networks

With the rapid expansion of computer networks during the past few years, security has become a crucial issue for modern computer systems. A good way to detect illegitimate use is through monitoring unusual user activity. Methods of intrusio...