Zobrazeno 1 - 10
of 68
pro vyhledávání: '"He, Jiangpeng"'
Autor:
Chen, Yuhao, He, Jiangpeng, Czarnecki, Chris, Vinod, Gautham, Mahmud, Talha Ibn, Raghavan, Siddeshwar, Ma, Jinge, Mao, Dayou, Nair, Saeejith, Xi, Pengcheng, Wong, Alexander, Delp, Edward, Zhu, Fengqing
Food computing is both important and challenging in computer vision (CV). It significantly contributes to the development of CV algorithms due to its frequent presence in datasets across various applications, ranging from classification and instance
Externí odkaz:
http://arxiv.org/abs/2409.01966
Food image classification is the fundamental step in image-based dietary assessment, which aims to estimate participants' nutrient intake from eating occasion images. A common challenge of food images is the intra-class diversity and inter-class simi
Externí odkaz:
http://arxiv.org/abs/2408.03922
Autor:
He, Jiangpeng, Chen, Yuhao, Vinod, Gautham, Mahmud, Talha Ibn, Zhu, Fengqing, Delp, Edward, Wong, Alexander, Xi, Pengcheng, AlMughrabi, Ahmad, Haroon, Umair, Marques, Ricardo, Radeva, Petia, Tang, Jiadong, Yang, Dianyi, Gao, Yu, Liang, Zhaoxiang, Jueluo, Yawei, Shi, Chengyu, Wang, Pengyu
The increasing interest in computer vision applications for nutrition and dietary monitoring has led to the development of advanced 3D reconstruction techniques for food items. However, the scarcity of high-quality data and limited collaboration betw
Externí odkaz:
http://arxiv.org/abs/2407.09285
Autor:
Huang, Yuning, Hassan, Mohamed Abul, He, Jiangpeng, Higgins, Janine, McCrory, Megan, Eicher-Miller, Heather, Thomas, Graham, Sazonov, Edward O, Zhu, Fengqing Maggie
Detecting an ingestion environment is an important aspect of monitoring dietary intake. It provides insightful information for dietary assessment. However, it is a challenging problem where human-based reviewing can be tedious, and algorithm-based re
Externí odkaz:
http://arxiv.org/abs/2405.07827
Image-based methods to analyze food images have alleviated the user burden and biases associated with traditional methods. However, accurate portion estimation remains a major challenge due to the loss of 3D information in the 2D representation of fo
Externí odkaz:
http://arxiv.org/abs/2404.12257
Food image classification systems play a crucial role in health monitoring and diet tracking through image-based dietary assessment techniques. However, existing food recognition systems rely on static datasets characterized by a pre-defined fixed nu
Externí odkaz:
http://arxiv.org/abs/2404.07507
A significant challenge in achieving ubiquitous Artificial Intelligence is the limited ability of models to rapidly learn new information in real-world scenarios where data follows long-tailed distributions, all while avoiding forgetting previously a
Externí odkaz:
http://arxiv.org/abs/2404.04476
Accurate identification and localization of anatomical structures of varying size and appearance in laparoscopic imaging are necessary to leverage the potential of computer vision techniques for surgical decision support. Segmentation performance of
Externí odkaz:
http://arxiv.org/abs/2403.17192
Image compression emerges as a pivotal tool in the efficient handling and transmission of digital images. Its ability to substantially reduce file size not only facilitates enhanced data storage capacity but also potentially brings advantages to the
Externí odkaz:
http://arxiv.org/abs/2403.06288
This paper explores the possibility of extending the capability of pre-trained neural image compressors (e.g., adapting to new data or target bitrates) without breaking backward compatibility, the ability to decode bitstreams encoded by the original
Externí odkaz:
http://arxiv.org/abs/2402.18862