Zobrazeno 1 - 10
of 661
pro vyhledávání: '"Patel, Vishal M"'
Federated Learning (FL) is a form of distributed learning that allows multiple institutions or clients to collaboratively learn a global model to solve a task. This allows the model to utilize the information from every institute while preserving dat
Externí odkaz:
http://arxiv.org/abs/2410.24181
Autor:
Safaei, Bardia, Patel, Vishal M.
Pre-trained vision-language models (VLMs) like CLIP have demonstrated impressive zero-shot performance on a wide range of downstream computer vision tasks. However, there still exists a considerable performance gap between these models and a supervis
Externí odkaz:
http://arxiv.org/abs/2410.22187
Autor:
Korkmaz, Yilmaz, Patel, Vishal M.
Magnetic Resonance Imaging (MRI) is one of the most important medical imaging modalities as it provides superior resolution of soft tissues, albeit with a notable limitation in scanning speed. The advent of deep learning has catalyzed the development
Externí odkaz:
http://arxiv.org/abs/2409.12401
Autor:
Korkmaz, Yilmaz, Patel, Vishal M.
Unpaired image-to-image translation is a challenging task due to the absence of paired examples, which complicates learning the complex mappings between the distinct distributions of the source and target domains. One of the most commonly used approa
Externí odkaz:
http://arxiv.org/abs/2409.12399
All-Weather Image Restoration (AWIR) under adverse weather conditions is a challenging task due to the presence of different types of degradations. Prior research in this domain relies on extensive training data but lacks the utilization of additiona
Externí odkaz:
http://arxiv.org/abs/2409.00263
Medical image segmentation has been traditionally approached by training or fine-tuning the entire model to cater to any new modality or dataset. However, this approach often requires tuning a large number of parameters during training. With the intr
Externí odkaz:
http://arxiv.org/abs/2408.06447
Recent vision-language pre-training models have exhibited remarkable generalization ability in zero-shot recognition tasks. Previous open-vocabulary 3D scene understanding methods mostly focus on training 3D models using either image or text supervis
Externí odkaz:
http://arxiv.org/abs/2407.09781
Referenced-based scene stylization that edits the appearance based on a content-aligned reference image is an emerging research area. Starting with a pretrained neural radiance field (NeRF), existing methods typically learn a novel appearance that ma
Externí odkaz:
http://arxiv.org/abs/2407.07220
Change detection in remote sensing images is an essential tool for analyzing a region at different times. It finds varied applications in monitoring environmental changes, man-made changes as well as corresponding decision-making and prediction of fu
Externí odkaz:
http://arxiv.org/abs/2407.06839
Autor:
Zeng, Yu, Patel, Vishal M., Wang, Haochen, Huang, Xun, Wang, Ting-Chun, Liu, Ming-Yu, Balaji, Yogesh
Personalized text-to-image generation models enable users to create images that depict their individual possessions in diverse scenes, finding applications in various domains. To achieve the personalization capability, existing methods rely on finetu
Externí odkaz:
http://arxiv.org/abs/2407.06187