Abstracts of the 3rd World Conference on Artificial Intelligence, Machine Learning and Data Science

Conference: 3rd World Conference on Artificial Intelligence, Machine Learning and Data Science
  • ISBN Print:
    978-81-970290-5-9
  • ISBN Online:
    978-81-970290-9-7
  • Conference Type:
    Virtual Conference
  • Conference Dates:
    May 23 - 24 , 2024
  • Venue:
    , Rome, Italy
  • Publisher:
    Eurasia Conferences

About the Book of Abstracts

Explore the Book of Abstracts for the 3rd World Conference on Artificial Intelligence, Machine Learning, and Data Science, held from May 23-24, 2024, in the enchanting city of Rome, Italy. This compilation not only showcases cutting-edge research and scholarly contributions across these vital fields but also highlights the interdisciplinary dialogues and innovative themes that emerged. Featuring insights from esteemed participants, including keynote speakers renowned in their respective disciplines, this collection encapsulates the spirit of collaboration and forward-thinking that characterized the conference. Delve into these pages to discover the rich tapestry of knowledge woven together at an event that continues to shape future directions in Artificial Intelligence, Machine Learning, and Data Science.

Abstracts

AI in Engineering: Solid Frameworks and Applications

Gunar Ernis

doi 10.62422/978-81-970290-9-7-001

Internet of Medical Things (IoMT): The Future of Healthcare

Prof.Tanzila Saba

doi 10.62422/978-81-970290-9-7-002

Survey on XAI: Different Approaches and Aspects

Raimondo Fanale

doi 10.62422/978-81-970290-9-7-003

Automatic extraction of SMPC document for IDMP data model construction using Open-Source base Model LLM RAG: A benchmark for Pharmaceutical Regulatory Affairs

Florian PEREME

doi 10.62422/978-81-970290-9-7-004

From Rights to Rationale: Assessing the Legal Grounds for an Autonomous Right to Explanation

Uchenna Nnawuchi, Dr Carlisle George, and Dr Florian Kammueller

doi 10.62422/978-81-970290-9-7-005

Applied Method of Anomaly Detection for Machine Health Prognosis

Yuvraj Patil

doi 10.62422/978-81-970290-9-7-006

Deep Learning-Based Segmentation for Plant Leaf Disease Identification

Olfa MZOUGH and Itheri Yahiaoui

doi 10.62422/978-81-970290-9-7-007

Impact of Artificial Intelligence Techniques and Green AI Applications for Sustainable Development

Amit Srivastava

doi 10.62422/978-81-970290-9-7-008

Fault Diagnosis in Wind Turbine Blades using Machine Learning Models through Filtered Cultivation Data

Manas Ranjan Sethi and Sudarsan Sahoo

doi 10.62422/978-81-970290-9-7-009

CharActER: a proposed AI for teaching Chinese the WRITE Way

Martin Q. Zhao and Andy D. Digh

doi 10.62422/978-81-970290-9-7-010

Deep Learning Across Disciplines: From Trajectory Recognition to Image Classification, and from Stock Market Forecasting to Signal System Prediction

Dayi Jin

doi 10.62422/978-81-970290-9-7-011

Caustics: A Differentiable, GPU Accelerated, Gravitational Lensing Simulator

Connor Stone

doi 10.62422/978-81-970290-9-7-012

The Dark Side of AI: Unveiling Ethical Dilemmas

Dr. Fatou Sankare

doi 10.62422/978-81-970290-9-7-013

A Digital Library to Promote Use of the World’s Theses and Dissertations

Dr. Edward A. Fox

doi 10.62422/978-81-970290-9-7-014