Applied Mathematics Research Papers

Robust Parameter Estimation in Computer Vision

Estimation techniques in computer vision applications must estimate accurate model parameters despite small-scale noise in the data, occasional large-scale measurement errors (outliers), and measurements from multiple populations in the sam...

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...

Optimal Coherent Point Selection for 3D Quality Inspection from Silhouette-Based Reconstructions

3D Geometric quality inspection involves assessing and comparing a reconstructed object to a predefined reference model or design that defines its expected volume. Achieving precise 3D object geometry reconstruction from multiple views can ...

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...

Application of Graph Structures in Computer Vision Tasks

On the one hand, the solution of computer vision tasks is associated with the development of various kinds of images or random fields mathematical models, i.e., algorithms, that are called traditional image processing. On the other hand, no...

Spatiotemporal patterns induced by four mechanisms in a tussock sedge model with discrete time and space variables

Abstract In this paper, we investigate the spatiotemporal patterns of a freshwater tussock sedge model with discrete time and space variables. We first analyze the kinetic system and show the parametric conditions for flip and Neimark–Sacke...

Robust regression methods for computer vision: A review

An Efficient Optimization Technique for Training Deep Neural Networks

Deep learning is a sub-branch of artificial intelligence that acquires knowledge by training a neural network. It has many applications in the field of banking, automobile industry, agriculture, and healthcare industry. Deep learning has pl...

Elastica and Computer Vision

Computer Vision – ECCV 2016

Retrieval of carbon dioxide vertical concentration profiles from satellite data using artificial neural networks

Abstract. In this paper, we derive vertical distributions of carbon dioxide atmospheric concentration from satellite data using a retrieval algorithm based on an artificial neural network (ANN) technique. Sensitivity studies were made to se...

Introduction to neural networks

Neural networks for nonlinear programming

The dynamics of the modified canonical nonlinear programming circuit are studied and how to guarantee the stability of the network's solution. By considering the total cocontent function, the solution of the canonical nonlinear programming ...

Topological Data Analysis: Foundations, Algorithms, and Emerging Applications

Topological data analysis (TDA) has evolved into a flexible and robust paradigm for obtaining qualitative, geometry-inspired insights from high-dimensional, noisy, and complex data. Grounded in algebraic topology, geometry, statistics, and ...

Treatment Effect Estimation in Survival Analysis Using Copula-Based Deep Learning Models for Causal Inference

This paper presents the use of Copula-based deep learning with Horvitz–Thompson (HT) weights and inverse probability of treatment weighting (IPTW) for estimating propensity scores in causal inference problems. This study compares the perfor...

Bi-Objective Portfolio Optimization Under ESG Volatility via a MOPSO-Deep Learning Algorithm

In this paper, we tackle a bi-objective optimization problem in which we aim to maximize the portfolio diversification and, at the same time, minimize the portfolio volatility, where the ESG (Environmental, Social, and Governance) informati...

Research on a Decision Prediction Method Based on Causal Inference and a Multi-Expert FTOPJUDGE Mechanism

Legal judgement prediction (LJP) is a crucial part of legal AI, and its goal is to predict the outcome of a case based on the information in the description of criminal facts. This paper proposes a decision prediction method based on causal...

Intelligent Distribution-Network Fault Handling via Cross-Modal Semantic Fusion and Knowledge-Graph Reasoning

Power distribution network fault handling imposes stringent requirements on both response timeliness and decision reliability. The high penetration of distributed renewable generation, the widespread deployment of power-electronic devices, ...

HIFU Tissue Degeneration Classification Based on Multifractal Detrending Fluctuation Analysis and Vision Transformer

For high-intensity focused ultrasound (HIFU) thermal ablation to be safe and effective, real-time, high-precision monitoring of tissue coagulative necrosis is essential. However, decoding the ultra-long, non-stationary radio frequency (RF) ...

Data Mining and Machine Learning

The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data in applications ranging from scientific discovery to business an...