Zobrazeno 1 - 10
of 440
pro vyhledávání: '"Jieren P"'
Autor:
Deng, Jieren, Hong, Hanbin, Palmer, Aaron, Zhou, Xin, Bi, Jinbo, Mahmood, Kaleel, Hong, Yuan, Aguiar, Derek
Randomized smoothing has become a leading method for achieving certified robustness in deep classifiers against l_{p}-norm adversarial perturbations. Current approaches for achieving certified robustness, such as data augmentation with Gaussian noise
Externí odkaz:
http://arxiv.org/abs/2405.16036
This paper presents Incremental Vision-Language Object Detection (IVLOD), a novel learning task designed to incrementally adapt pre-trained Vision-Language Object Detection Models (VLODMs) to various specialized domains, while simultaneously preservi
Externí odkaz:
http://arxiv.org/abs/2403.01680
Autor:
Deng, Jieren, Palmer, Aaron, Mahmood, Rigel, Rathbun, Ethan, Bi, Jinbo, Mahmood, Kaleel, Aguiar, Derek
Achieving resiliency against adversarial attacks is necessary prior to deploying neural network classifiers in domains where misclassification incurs substantial costs, e.g., self-driving cars or medical imaging. Recent work has demonstrated that rob
Externí odkaz:
http://arxiv.org/abs/2402.15586
Newly developed diffusion-based techniques have showcased phenomenal abilities in producing a wide range of high-quality images, sparking considerable interest in various applications. A prevalent scenario is to generate new images based on a subject
Externí odkaz:
http://arxiv.org/abs/2312.02521
In this work, we present a novel framework for camera relocation in autonomous vehicles, leveraging deep neural networks (DNN). While existing literature offers various DNN-based camera relocation methods, their deployment is hindered by their high c
Externí odkaz:
http://arxiv.org/abs/2312.00316
Autor:
Jieren Xie, Guanghua Xu, Xiaobi Chen, Xun Zhang, Ruiquan Chen, Zengyao Yang, Churui Fang, Peiyuan Tian, Qingqiang Wu, Sicong Zhang
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-19 (2024)
Abstract This paper presents a novel approach to the phase space reconstruction technique, fractional-order phase space reconstruction (FOSS), which generalizes the traditional integer-order derivative-based method. By leveraging fractional derivativ
Externí odkaz:
https://doaj.org/article/aafc2b64d38946d0a22e8f1d4b1b6802
The bokeh effect is an artistic technique that blurs out-of-focus areas in a photograph and has gained interest due to recent developments in text-to-image synthesis and the ubiquity of smart-phone cameras and photo-sharing apps. Prior work on render
Externí odkaz:
http://arxiv.org/abs/2306.08251
Distilling the structured information captured in feature maps has contributed to improved results for object detection tasks, but requires careful selection of baseline architectures and substantial pre-training. Self-distillation addresses these li
Externí odkaz:
http://arxiv.org/abs/2303.05015
With the development of various applications, such as social networks and knowledge graphs, graph data has been ubiquitous in the real world. Unfortunately, graphs usually suffer from being absent due to privacy-protecting policies or copyright restr
Externí odkaz:
http://arxiv.org/abs/2302.07524
Federated Learning (FL) is a distributed machine learning framework to alleviate the data silos, where decentralized clients collaboratively learn a global model without sharing their private data. However, the clients' Non-Independent and Identicall
Externí odkaz:
http://arxiv.org/abs/2209.13803