Academic Articles & Research Papers

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...

AN EXTRACTION OF KEY VARIABLESFOR LONG-TERM TRENDS USING A MODIFIEDCROSS-IMPACT MATRIX

The traditional approach to forecasting lies in the assumption that, byapplying a set of powerful analytic tools, the future could be predictedaccurately enough to choose an appropriate strategic direction for it. Theprocess often involves ...

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...

Bridging the performance–efficiency gap: a resource-efficient hybrid DL-ML framework for jackfruit disease detection

Complex environment variability and limited computational resources in agricultural settings create challenges in automated detection in tropical regions, where jackfruit diseases pose major threats to harvest productivity and food security...

Computer Vision – ECCV 2024

Reliable Parkinson’s Disease Detection by Analyzing Handwritten Drawings: Construction of an Unbiased Cascaded Learning System Based on Feature Selection and Adaptive Boosting Model

Parkinson's disease (PD) is the second most common neurodegenerative disease of central nervous system (CNS). Till now, there is no definitive clinical examination that can diagnose a PD patient. However, it has been reported that PD patien...

Sequential Normalization: Embracing Smaller Sample Sizes for Normalization

Normalization as a layer within neural networks has over the years demonstrated its effectiveness in neural network optimization across a wide range of different tasks, with one of the most successful approaches being that of batch normaliz...

An Introduction to 3D Computer Vision Techniques and Algorithms

present basic low-level image processing operations for image matching, including a separate chapter on image matching algorithms; \n explain scale-space vision, as well as space reconstruction and multiview integration; \n demonstrate a va...

Scale Space and PDE Methods in Computer Vision

MaskDis R‐CNN: An instance segmentation algorithm with adversarial network for herd pigs

Abstract The current instance segmentation method can achieve satisfactory results in common scenarios. However, under the overlap or partial occlusion between targets caused by the complex scenes, accurate segmentation of pigs remains a ch...

Key Technologies of Vehicle Active Safety System Based on Computer Vision

Due to the increase in the number of urban vehicles and the irregular driving behavior of drivers, urban accidents frequently occur, causing serious casualties and economic losses. Active vehicle safety systems can monitor vehicle status an...

Early Termination of CU Partition Based on Boosting Neural Network for 3D-HEVC Inter-Coding

As an extension of the High Efficiency Video Coding (HEVC) standard, the 3D-HEVC needs to encode multiple texture videos and depth maps components. In the 3D-HEVC inter-coding test model, a large variety of Coding Unit (CU) sizes are adopte...

The NWRD Dataset: An Open-Source Annotated Segmentation Dataset of Diseased Wheat Crop

Wheat stripe rust disease (WRD) is extremely detrimental to wheat crop health, and it severely affects the crop yield, increasing the risk of food insecurity. Manual inspection by trained personnel is carried out to inspect the disease spre...

Computer Vision – ECCV 2006

Computer Vision – ECCV 2022 Workshops

Mastering OpenCV with Practical Computer Vision Projects

Each chapter in the book is an individual project and each project is constructed with step-by-step instructions, clearly explained code, and includes the necessary screenshots. You should have basic OpenCV and C/C++ programming experience ...

Pattern Recognition and Computer Vision

Soft–Hard Attention U-Net Model and Benchmark Dataset for Multiscale Image Shadow Removal

Effective shadow removal is pivotal in enhancing visual image quality in applications such as computer vision and digital photography. During the last decades physics-based and machine learning methodologies have been proposed; however, mos...

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...

A human activity recognition method based on Vision Transformer

Abstract Human activity recognition has a wide range of applications in various fields, such as video surveillance, virtual reality and human–computer intelligent interaction. It has emerged as a significant research area in computer vision...