Zobrazeno 1 - 10
of 15 620
pro vyhledávání: '"A. Vamsi"'
Autor:
Marquette, Wade, Schultz, Kyle, Jonnalagadda, Vamsi, Wong, Benjamin, Garbini, Joseph, Devasia, Santosh
Visual inspection of confined spaces such as aircraft wings is ergonomically challenging for human mechanics. This work presents a novel crane robot that can travel the entire span of the aircraft wing, enabling mechanics to perform inspection from o
Externí odkaz:
http://arxiv.org/abs/2412.10973
Autor:
Wei, Rongzhe, Li, Mufei, Ghassemi, Mohsen, Kreačić, Eleonora, Li, Yifan, Yue, Xiang, Li, Bo, Potluru, Vamsi K., Li, Pan, Chien, Eli
Large Language Models are trained on extensive datasets that often contain sensitive, human-generated information, raising significant concerns about privacy breaches. While certified unlearning approaches offer strong privacy guarantees, they rely o
Externí odkaz:
http://arxiv.org/abs/2412.08559
Autor:
Wang, Hao, Zhu, Wenhui, Dong, Xuanzhao, Chen, Yanxi, Li, Xin, Qiu, Peijie, Chen, Xiwen, Vasa, Vamsi Krishna, Xiong, Yujian, Dumitrascu, Oana M., Razi, Abolfazl, Wang, Yalin
In this work, we propose Many-MobileNet, an efficient model fusion strategy for retinal disease classification using lightweight CNN architecture. Our method addresses key challenges such as overfitting and limited dataset variability by training mul
Externí odkaz:
http://arxiv.org/abs/2412.02825
Deep Learning (DL) techniques are increasingly applied in scientific studies across various domains to address complex research questions. However, the methodological details of these DL models are often hidden in the unstructured text. As a result,
Externí odkaz:
http://arxiv.org/abs/2411.09269
Autor:
Cheng, Longbiao, Pandey, Ashutosh, Xu, Buye, Delbruck, Tobi, Ithapu, Vamsi Krishna, Liu, Shih-Chii
Deep learning-based speech enhancement (SE) methods often face significant computational challenges when needing to meet low-latency requirements because of the increased number of frames to be processed. This paper introduces the SlowFast framework
Externí odkaz:
http://arxiv.org/abs/2411.02019
Autor:
Ghassemi, Mohsen, Mishler, Alan, Dalmasso, Niccolo, Zhang, Luhao, Potluru, Vamsi K., Balch, Tucker, Veloso, Manuela
Conditional demographic parity (CDP) is a measure of the demographic parity of a predictive model or decision process when conditioning on an additional feature or set of features. Many algorithmic fairness techniques exist to target demographic pari
Externí odkaz:
http://arxiv.org/abs/2410.14029
Autor:
Bobba, Kumar Srinivas, K, Kartheeban, Sai, Vamsi Krishna, Bugga, Dinesh, Bolla, Vijaya Mani Surendra
This project proposes the development of a comprehensive real-time biodiversity monitoring system that harnesses sound data through a network of acoustic sensors and advanced artificial intelligence algorithms. The system analyzes sound recordings fr
Externí odkaz:
http://arxiv.org/abs/2410.12897
In recent years, significant progress has been made in the medical image analysis domain using convolutional neural networks (CNNs). In particular, deep neural networks based on a U-shaped architecture (UNet) with skip connections have been adopted f
Externí odkaz:
http://arxiv.org/abs/2410.11578
Hamilton-Jacobi (HJ) reachability analysis is a powerful framework for ensuring safety and performance in autonomous systems. However, existing methods typically rely on a white-box dynamics model of the system, limiting their applicability in many p
Externí odkaz:
http://arxiv.org/abs/2410.07796
Recent developments in generative models have demonstrated its ability to create high-quality synthetic data. However, the pervasiveness of synthetic content online also brings forth growing concerns that it can be used for malicious purposes. To ens
Externí odkaz:
http://arxiv.org/abs/2409.14700