Academic Articles & Research Papers

A novel nondestructive detection approach for seed cotton lint percentage using deep learning

Abstract Background The lint percentage of seed cotton is one of the most important parameters for evaluating seed cotton quality and affects its price. The traditional measuring method of lint percentage is labor-intensive and time-consumi...

Geo-Temporal Selective Approach for Dynamic Depth Estimation in Outdoor Object Detection and Distance Measurement

Accurate depth information is crucial for various computer vision applications such as augmented reality, 3D modeling, and autonomous vehicles. Recent advancements have significantly improved both supervised and self-supervised methods for ...

Unconstrained Bilingual Scene Text Reading Using Octave as a Feature Extractor

Reading text and unified text detection and recognition from natural images are the most challenging applications in computer vision and document analysis. Previously proposed end-to-end scene text reading methods do not consider the freque...

Hyperspectral Methane Plume Segmentation Through Foundation Computer Vision Models

Efficient large-scale monitoring of methane emissions is crucial for sustainable environmental management, necessitating advanced remote sensing techniques that process hyperspectral imagery to provide detailed insights into the Earth&#x201...

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...

Design and Implementation of a Ball-Plate Control System and Python Script for Educational Purposes in STEM Technologies

This paper presents the process of designing, fabricating, assembling, programming and optimizing a prototype nonlinear mechatronic Ball-Plate System (BPS) as a laboratory platform for engineering education STEM. Due to the nonlinearity and...

A Review of Basketball Shooting Analysis Based on Artificial Intelligence

Artificial Intelligence (AI) has promising applications in basketball shooting analysis, as it can help basketball athletes improve their shooting techniques and accuracy, thereby enhancing the effectiveness of both games and training sessi...

Using cascade CNN-LSTM-FCNs to identify AI-altered video based on eye state sequence

Deep learning is notably successful in data analysis, computer vision, and human control. Nevertheless, this approach has inevitably allowed the development of DeepFake video sequences and images that could be altered so that the changes ar...

Lipid vesicle shape analysis from populations using light video microscopy and computer vision.

We present a method for giant lipid vesicle shape analysis that combines manually guided large-scale video microscopy and computer vision algorithms to enable analyzing vesicle populations. The method retains the benefits of light microscop...

Fruit freshness detection based on multi-task convolutional neural network

Background: Fruit freshness detection by computer vision is essential for many agricultural applications, e.g., automatic harvesting and supply chain monitoring. This paper proposes to use the multi-task learning (MTL) paradigm to build a d...

Computer Vision for X-Ray Testing

Three-Dimensional Computer Vision

Fundamentals of Computer Vision

Computer vision has widespread and growing application including robotics, autonomous vehicles, medical imaging and diagnosis, surveillance, video analysis, and even tracking for sports analysis. This book equips the reader with crucial mat...

2012 IEEE Conference on Computer Vision and Pattern Recognition

Color of Salmon Fillets By Computer Vision and Sensory Panel

Computer Vision and Natural Constraints

Computer vision, the automatic construction of scene descriptions from image input data, has just entered its second decade. Approaches have varied widely, especially in the amounts of symbolic, domain-dependent knowledge and inference that...

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...

Kernel Methods in Computer Vision

Over the last years, kernel methods have established themselves as powerful tools for computer vision researchers as well as for practitioners. In this tutorial, we give an introduction to kernel methods in computer vision from a geometric ...

Federated Learning in Computer Vision

Federated Learning (FL) has recently emerged as a novel machine learning paradigm allowing to preserve privacy and to account for the distributed nature of the learning process in many real-world settings. Computer vision tasks deal with hu...

Automated estimation of cementitious sorptivity via computer vision

Monitoring water uptake in cementitious systems is crucial to assess their durability against corrosion, salt attack, and freeze-thaw damage. However, gauging absorption currently relies on labor-intensive and infrequent weight measurements...