In this article, we propose a machine learning based fine-grained vehicle classification
method VehiClassNet, which effectively solves the challenges of precise vehicle recognition …

In this paper, we compare and analyse the effectiveness of deep learning models such as
AlexNet, Vgg, GoogleNet and MobileNet in the task of pneumonia image classification …

In this paper, we compare and analyse the effectiveness of deep learning models such as
AlexNet, Vgg, GoogleNet and MobileNet in the task of pneumonia image classification …

Synthetic Aperture Radar has been extensively used in numerous fields and can gather a
wealth of information about the area of interest. This large-scene data-intensive technology …

This paper proposed a comprehensive mixed-methods framework with varied samples of
older adults, including user experience, usability assessments, and in-depth interviews with …

With the development of industrial automation, the accurate prediction of the health state of
equipment becomes particularly important. This study aims to address the problem of …

Federated Learning (FL) is a privacy-focused revolutionary approach distributed paradigm
that supports considerable devices to train a shared model collaboratively without …

Federated Learning (FL) is a distributed training paradigm wherein participants collaborate
to build a global model while ensuring the privacy of the involved data, which remains stored …

Federated learning (FL) is an emerging machine learning paradigm designed to address the
challenge of the data island while preserving data privacy. In this approach, multiple clients …

This paper introduces" SeamCarver," a LLM-enhanced method that redefines image
resizing. SeamCarver addresses the limitations of traditional seam carving with static pre …