Academic Articles & Research Papers

Frozen Weights as Prior for Parameter-Efficient Fine-Tuning

In the fields of natural language processing and computer vision, the emergence of large pre-trained models has led to the adoption of fine-tuning them for downstream tasks as an important paradigm. However, the full fine-tuning approach of...

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...

COVID-19 Control by Computer Vision Approaches: A Survey

The COVID-19 pandemic has triggered an urgent call to contribute to the fight against an immense threat to the human population. Computer Vision, as a subfield of artificial intelligence, has enjoyed recent success in solving various comple...

Introductory Techniques for 3-D Computer Vision

From the Publisher: FEATURES: Provides a guide to well-tested theory and algorithms including solutions of problems encountered in modern computer vision. Contains many practical hints highlighted in the book. Develops two parallel ...

Calibration and Orientation of Cameras in Computer Vision

A Comprehensive Joint Learning System to Detect Skin Cancer

Skin, the body’s biggest organ and a barrier against heat, light, damage, and infection can be affected by many diseases. However, a correct diagnosis can lead to proper treatment. Skin diseases must be identified early to reduce ski...

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...

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...

Monitoring the spread of a pathogenic insect on vineyards using UAS

Globalisation has contributed to rapid economic growth but has also exposed vulnerabilities such as the spread of pests in agriculture. An example is the Popillia Japonica Newman beetle, introduced to Italy in 2014, which has caused signifi...

Generalized Vision-Based Detection, Identification and Pose Estimation of Lamps for BIM Integration

This paper introduces a comprehensive approach based on computer vision for the automatic detection, identification and pose estimation of lamps in a building using the image and location data from low-cost sensors, allowing the incorporati...

Quaternions in Computer Vision and Robotics

Computer vision and robotics suffer from not having good tools for manipulating three-dimensional objects. Vectors, coordinate geometry, and trigonometry all have deficiencies. Quaternions can be used to solve many of these problems. Many p...

Gestalt Theory and Computer Vision

In the Wertheimer programme there are two kinds of organizing laws. The rst kind are grouping laws which, starting from atomic and local data, recursively construct larger groups in the perceived image. Each grouping law focuses on a single...

Image fusion method based on simultaneous sparse representation with non‐subsampled contourlet transform

The image fusion method based on sparse representation in the single‐scale image domain has produced better fusion results than the classic methods based on multi‐scale analysis nowadays. However, due to the limited number of dictionary ato...

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...

Enhanced Combined Techniques for Interval-Valued Intuitionistic Fuzzy Multiple-Attribute Group Decision-Making and Applications to Quality Evaluation of Large-Scale Multi-View 3D Reconstruction

With the widespread application of computer vision in many fields, quickly and accurately obtaining the three-dimensional information covered by the target object has become a concern in the field of vision research. Large scale multi view ...

Sparse Representation for Computer Vision and Pattern Recognition

Techniques from sparse signal representation are beginning to see significant impact in computer vision, often on nontraditional applications where the goal is not just to obtain a compact high-fidelity representation of the observed signal...

Information fusion in computer vision using the fuzzy integral

A method of evidence fusion, based on the fuzzy integral, is developed. This technique nonlinearly combines objective evidence, in the form of a fuzzy membership function, with subjective evaluation of the worth of the sources with respect ...

Deep Learning for Understanding Satellite Imagery: An Experimental Survey

Translating satellite imagery into maps requires intensive effort and time, especially leading to inaccurate maps of the affected regions during disaster and conflict. The combination of availability of recent datasets and advances in compu...