A low-dimensional voice latent space derived from deep learning captures speaker-identity representations in the temporal voice areas and supports reconstruction of voices preserving identity ...

The future of trading belongs to ecosystems where algorithms and informed human decision making work together in disciplined ...

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...

Abstract: The increasing use of unmanned aerial vehicles (UAVs) highlights the need for robust classification systems. This study explores the impact of noise on UAV classification accuracy using ...

Ashutosh Agarwal is a specialist who connects analytics with practical strategy, who stands out in the era of digital ...

Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive ...

Introduction: In recent years, advancements in machine learning and electronic stethoscope technology have enabled high-precision recording and analysis of lung sounds, significantly enhancing ...

Abstract: Image classification is one of the central research in machine learning that has wide application in many fields. Many factors can adversely impact the classification accuracy, including ...

1 Department of Computer Science, Rutgers University, New Brunswick, NJ, USA. 2 Department of Computer Science, Rochester Institute of Technology, Rochester, NY, USA. This paper presents a ...

Background: Knee osteoarthritis (KOA) constitutes the prevailing manifestation of arthritis. Radiographs function as a common modality for primary screening; however, traditional X-ray evaluation of ...

Code in which an initial approach to decision trees and bagging will be made, and an attempt will be made to ensure that the model can be trained with any dataset coming from Kaggle (for this, we will ...