Abstract: Implicit Neural Representations have gained prominence as a powerful framework for capturing complex data modalities, encompassing a wide range from 3D shapes to images and audio. Within the ...
Abstract: Self-supervised models are shaping the future of point cloud processing by minimizing reliance on labeled data and addressing the challenges associated with point cloud annotation.
Abstract: Quantum Computing (QC) technology and Deep Learning (DL) science have garnered significant attention for their potential to revolutionize computation. This paper introduces the basic ...
Abstract: This paper presents a maximum power point tracking (MPPT) methodology utilizing machine learning (ML) to precisely monitor the maximum power output of a photovoltaic (PV) panel. This ...
Abstract: Self-supervised learning of point cloud aims to leverage unlabeled 3D data to learn meaningful representations without reliance on manual annotations. However, current approaches face ...
Abstract: Tracking the human arm is essential for a variety of applications, including medical rehabilitation, sports analysis, and human-computer interaction. Current vision-based and wearable sensor ...
Abstract: All-in-one image restoration, which seeks to handle multiple types of degradation within a unified model, has become a prominent research topic in computer vision. While existing deep ...
A secure GUI-based banking application built with Java Swing and SQLite using NetBeans IDE. This project demonstrates how to integrate desktop applications with a database to manage financial ...
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