Cross-task multi-branch vision transformer for facial expression and mask wearing classification
With wearing masks becoming a new cultural norm, facial expression recognition (FER)
while taking masks into account has become a significant challenge. In this paper, we …
while taking masks into account has become a significant challenge. In this paper, we …
Utilizing deep learning to optimize software development processes
This study explores the application of deep learning technologies in software development
processes, particularly in automating code reviews, error prediction, and test generation to …
processes, particularly in automating code reviews, error prediction, and test generation to …
A comparative study on enhancing prediction in social network advertisement through data augmentation
Q Yang, P Li, X Xu, Z Ding, W Zhou… - 2024 4th International …, 2024 - ieeexplore.ieee.org
In the ever-evolving landscape of social network advertising, the volume and accuracy of
data play a critical role in the performance of predictive models. However, the development …
data play a critical role in the performance of predictive models. However, the development …
Exploring diverse methods in visual question answering
P Li, Q Yang, X Geng, W Zhou, Z Ding… - arXiv preprint arXiv …, 2024 - arxiv.org
This study explores innovative methods for improving Visual Question Answering (VQA)
using Generative Adversarial Networks (GANs), autoencoders, and attention mechanisms …
using Generative Adversarial Networks (GANs), autoencoders, and attention mechanisms …
Online learning of multiple tasks and their relationships: Testing on spam email data and eeg signals recorded in construction fields
This paper examines an online multi-task learning (OMTL) method, which processes data
sequentially to predict labels across related tasks. The framework learns task weights and …
sequentially to predict labels across related tasks. The framework learns task weights and …
Quantizing heavy-tailed data in statistical estimation:(near) minimax rates, covariate quantization, and uniform recovery
Modern datasets often exhibit heavy-tailed behavior, while quantization is inevitable in
digital signal processing and many machine learning problems. This paper studies the …
digital signal processing and many machine learning problems. This paper studies the …
High dimensional statistical estimation under uniformly dithered one-bit quantization
In this paper, we propose a uniformly dithered 1-bit quantization scheme for high-
dimensional statistical estimation. The scheme contains truncation, dithering, and …
dimensional statistical estimation. The scheme contains truncation, dithering, and …
Mapping new realities: Ground truth image creation with pix2pix image-to-image translation
Generative Adversarial Networks (GANs) have significantly advanced image processing,
with Pix2Pix being a notable framework for image-to-image translation. This paper explores …
with Pix2Pix being a notable framework for image-to-image translation. This paper explores …
Deep representation learning for multi-functional degradation modeling of community-dwelling aging population
As the aging population grows, particularly for the baby boomer generation, the United
States is witnessing a significant increase in the elderly population experiencing …
States is witnessing a significant increase in the elderly population experiencing …
Understanding implicit regularization in over-parameterized single index model
In this article, we leverage over-parameterization to design regularization-free algorithms for
the high-dimensional single index model and provide theoretical guarantees for the induced …
the high-dimensional single index model and provide theoretical guarantees for the induced …