Academic Articles & Research Papers

Speeding Up Semantic Instance Segmentation by Using Motion Information

Environment perception and understanding represent critical aspects in most computer vision systems and/or applications. State-of-the-art techniques to solve this vision task (e.g., semantic instance segmentation) require either dedicated h...

Computer Vision and Pattern Recognition 2020

This special issue covers a wide range of topics from the area of Computer Vision, Pattern Recognition, and Machine Learning.This breadth of scope is reflected by the papers included in this special issue, which touch topics including geome...

Advances in Computer Vision

Contents: A. Hanson, E. Riseman, The Visions Image Understanding System. J. Aloimonos, C. Brown, Robust Computation of Intrinsic Images from Multiple Cues. A. Waxman, K. Wohn, Image Flow Theory: A Framework for 3-D Inference From Time-Varyi...

Impact of Water Depth on Subway Emergency Evacuation in Flood Scenarios

[Objective] Evacuation bottlenecks for subway stations in flood scenarios are investigated to enhance subway station personnel evacuation efficiency under water inundation and backflow conditions, and provide insights for developing subway ...

DualSight: multi-stage instance segmentation framework for improved precision

Abstract Powder properties, particularly their morphology (which includes size, shape, surface roughness, etc.), play a critical role in the quality of cold spray additively manufactured materials. A change in feedstock powder morphology ca...

HawkEye: AI-Driven Software for Objective Analysis and Characterization of Nodular Cast Iron Microstructures

Metallographic evaluation of nodular cast iron is crucial for quality control in the foundry industry. Traditionally, this process relies on experts who visually interpret microscopic images. This study introduces HawkEye, a comprehensive s...

Machine Learning in Computer Vision

During last few years the computer applications have gone dramatic transformation from simple data processing to machine learning, thanks to the availability and accessibility of huge volume of data collected through sensors and internet. T...

Parallax attention stereo matching network based on the improved group-wise correlation stereo network

Recent stereo matching methods, especially end-to-end deep stereo matching networks, have achieved remarkable performance in the fields of autonomous driving and depth sensing. However, state-of-the-art stereo algorithms, even with the deep...

Does manufacturing specialization matter? Transfer accuracy of static surgical guides produced by general-purpose and dental-specific additive workflows: A paired in vitro study.

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...

Crowdsourcing in Computer Vision

Computer vision systems require large amounts of manually annotated data to properly learn challenging visual concepts. Crowdsourcing platforms offer an inexpensive method to capture human knowledge and understanding, for a vast number of v...

Computer vision and machine‐learning techniques for quantification and predictive modeling of intracellular anticancer drug delivery by nanocarriers

Abstract The field of cancer nanomedicine has made significant progress, but its clinical translation is impeded by many challenges, such as the difficulty in analyzing intracellular anticancer drug release by the nanocarriers due to the la...

Enhanced gradient learning for deep neural networks

Abstract Deep neural networks have achieved great success in both computer vision and natural language processing tasks. How to improve the gradient flows is crucial in training very deep neural networks. To address this challenge, a gradie...

Open real-time, non-invasive fish detection and size estimation utilizing binocular camera system in a Portuguese river affected by hydropeaking

The need for efficient approaches to track and assess fish behavior in rivers impacted by hydropeaking is increasing. Nonetheless, employing an automated camera system for underwater monitoring requires that the algorithms function under hi...

Handbook of computer vision and applications

Contents of Volume One: Preface. Contributors. B. Jahne, Introduction. Illumination and Image Formation. H. Hausecker, Radiation. H. Hausecker, Interaction of Radiation with Matter. P. Geisler, Geometric and Wave Optics. H. Hausecker, Radio...

Neural Networks for River Flow Prediction

The surface‐water hydrographs of rivers exhibit large variations due to many natural phenomena. One of the most commonly used approaches for interpolating and extending streamflow records is to fit observed data with an analytic power model...

Bayesian Regularization of Neural Networks

Bayesian regularized artificial neural networks (BRANNs) are more robust than standard back-propagation nets and can reduce or eliminate the need for lengthy cross-validation. Bayesian regularization is a mathematical process that converts ...

Shear banding and flow instabilities in wormlike micelles: Modelling and mechanisms – A review

Worm-like micelles (WLMs) are dynamic, self-assembling supramolecular structures that exhibit complex viscoelastic behaviour due to their ability to undergo reversible scission, fusion, branching, and sequence rearrangement. This review pro...

Tailoring Mission Effectiveness and Efficiency of a Ground Vehicle Using Exergy-Based Model Predictive Control (MPC)

To ensure dominance over a multi-domain battlespace, energy and power utilization must be accurately characterized for the dissimilar operational conditions. Using MATLAB/Simulink in combination with multiple neural networks, we created a m...

Dual-Channel Dynamic Gated Spatio-Temporal Graph for Traffic Flow Forecasting

Traffic flow forecasting is a critical and essential technology in the field of Intelligent Transportation Systems (ITS), as it plays a pivotal role in optimizing traffic management, improving road safety, and enhancing the overall efficien...