Academic Articles & Research Papers

Artificial Intelligence in Routine IVF Practice

Background: Artificial Intelligence (AI) has emerged as a transformative tool in in vitro fertilization (IVF) as it has done in other sectors. In IVF, AI offers advancements in embryo selection, treatment personalization, and outcome predic...

TRAMON: An automated traffic monitoring system for high density, mixed and lane-free traffic

This paper introduces a new visual dataset and framework to facilitate computer-vision-based traffic monitoring in high density, mixed and lane-free traffic (TRAMON). While there are advanced deep learning algorithms that can detect and tra...

SnowMapPy: An automated GEE Python tool for snow cover mapping and monitoring in the Moroccan Atlas Mountains

SnowMapPy is an open-source Python-based package developed to streamline the collection, processing, and analysis of MODIS snow cover data from Terra and Aqua satellites. By automating essential steps, including data clipping, reprojection,...

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

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...

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...

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 ...

Deep learning-enabled medical computer vision

A decade of unprecedented progress in artificial intelligence (AI) has demonstrated the potential for many fields-including medicine-to benefit from the insights that AI techniques can extract from data. Here we survey recent progress in th...

Deep Learning: A Practitioner's Approach

Although interest in machine learning has reached a high point, lofty expectations often scuttle projects before they get very far. How can machine learningespecially deep neural networksmake a real difference in your organization? This han...

A Machine Learning-Oriented Survey on Tiny Machine Learning

The emergence of Tiny Machine Learning (TinyML) has positively revolutionized the field of Artificial Intelligence by promoting the joint design of resource-constrained IoT hardware devices and their learning-based software architectures. T...

Machine learning for ecosystem services

Recent developments in machine learning have expanded data-driven modelling (DDM) capabilities, allowing artificial intelligence to infer the behaviour of a system by computing and exploiting correlations between observed variables within i...

Perspectives in machine learning for wildlife conservation

Inexpensive and accessible sensors are accelerating data acquisition in animal ecology. These technologies hold great potential for large-scale ecological understanding, but are limited by current processing approaches which inefficiently d...

Explainable machine learning for predicting clinical outcomes in HIV/TB co-infection: a comparative retrospective study

Abstract Background HIV/TB co-infection presents substantial public-health challenges, showing greater treatment-failure and mortality rates than tuberculosis alone. Recent advances in machine learning (ML) provide a robust means of identif...

IoT Device Identification Using Directional Packet Length Sequences and 1D-CNN

With the large-scale application of the Internet of Things (IoT), security issues have become increasingly prominent. Device identification is an effective way to secure IoT environment by quickly identifying the category or model of device...

Machine learning for combustion

Combustion science is an interdisciplinary study that involves nonlinear physical and chemical phenomena in time and length scales, including complex chemical reactions and fluid flows. Combustion widely supplies energy for powering vehicle...

Machine Learning for Fluid Mechanics

The field of fluid mechanics is rapidly advancing, driven by unprecedented volumes of data from experiments, field measurements, and large-scale simulations at multiple spatiotemporal scales. Machine learning (ML) offers a wealth of techniq...

Surface circulation properties in the eastern Mediterranean emphasized using machine learning methods

The eastern Mediterranean surface circulation is highly energetic and composed of structures interacting stochastically. However, some main features are still debated, and the behavior of some fine-scale dynamics and their role in shaping t...

Multi-Resolution and Multi-Temporal Satellite Remote Sensing Analysis to Understand Human-Induced Changes in the Landscape for the Protection of Cultural Heritage: The Case Study of the MapDam Project, Syria

This study presents a multi-resolution and multi-temporal remote sensing approach to assess human-induced changes in cultural landscapes, with a focus on the archaeological site of Amrit (Syria) within the MapDam project. By integrating sat...

The Integration of Cone Beam Computed Tomography, Artificial Intelligence, Augmented Reality, and Virtual Reality in Dental Diagnostics, Surgical Planning, and Education: A Narrative Review

(1) Background: Advancements in dental imaging technologies have significantly transformed diagnostic and surgical practices. The integration of cone beam computed tomography (CBCT), artificial intelligence (AI), augmented reality (AR), and...

Ranking-Based Case Retrieval with Graph Neural Networks in Process-Oriented Case-Based Reasoning

In Process-Oriented Case-Based Reasoning (POCBR), experiential knowledge from previous problem-solving situations is retrieved from a case base to be reused for upcoming problems. The task of retrieval is approached in previous work by usin...