no code implementations • 7 May 2024 • Raiyan Rahman, Christopher Indris, Goetz Bramesfeld, Tianxiao Zhang, Kaidong Li, Xiangyu Chen, Ivan Grijalva, Brian McCornack, Daniel Flippo, Ajay Sharda, Guanghui Wang
In this study, we trained and evaluated four real-time semantic segmentation models and three object detection models specifically for aphid cluster segmentation and detection.
no code implementations • 10 Aug 2023 • Tianxiao Zhang, Kaidong Li, Xiangyu Chen, Cuncong Zhong, Bo Luo, Ivan Grijalva, Brian McCornack, Daniel Flippo, Ajay Sharda, Guanghui Wang
To facilitate the use of machine learning models, we further process the images by cropping them into patches, resulting in a labeled dataset comprising 151, 380 image patches.
no code implementations • 17 Jul 2023 • Raiyan Rahman, Christopher Indris, Tianxiao Zhang, Kaidong Li, Brian McCornack, Daniel Flippo, Ajay Sharda, Guanghui Wang
We have collected and labeled a large aphid image dataset in the field, and propose the use of real-time semantic segmentation models to segment clusters of aphids.
no code implementations • 12 Jul 2023 • Tianxiao Zhang, Kaidong Li, Xiangyu Chen, Cuncong Zhong, Bo Luo, Ivan Grijalva Teran, Brian McCornack, Daniel Flippo, Ajay Sharda, Guanghui Wang
Aphids are one of the main threats to crops, rural families, and global food security.
1 code implementation • 22 Oct 2022 • Xiangyu Chen, Qinghao Hu, Kaidong Li, Cuncong Zhong, Guanghui Wang
After carefully examining the self-attention modules, we discover that the number of trivial attention weights is far greater than the important ones and the accumulated trivial weights are dominating the attention in Vision Transformers due to their large quantity, which is not handled by the attention itself.
1 code implementation • CVPR 2022 • Kaidong Li, Ziming Zhang, Cuncong Zhong, Guanghui Wang
Deep neural networks for 3D point cloud classification, such as PointNet, have been demonstrated to be vulnerable to adversarial attacks.
1 code implementation • 1 Feb 2022 • Xi Mo, Xiangyu Chen, Cuncong Zhong, Rui Li, Kaidong Li, Usman Sajid
Mean field approximation methodology has laid the foundation of modern Continuous Random Field (CRF) based solutions for the refinement of semantic segmentation.
1 code implementation • 26 Apr 2021 • Kaidong Li, Nina Y. Wang, Yiju Yang, Guanghui Wang
A super-class branch (SCB), trained on super-class labels, is introduced to guide finer class prediction.
no code implementations • 22 Apr 2021 • Kaidong Li, Mohammad I. Fathan, Krushi Patel, Tianxiao Zhang, Cuncong Zhong, Ajay Bansal, Amit Rastogi, Jean S. Wang, Guanghui Wang
This work can serve as a baseline for future research in polyp detection and classification.
no code implementations • 15 Oct 2020 • Wenchi Ma, Miao Yu, Kaidong Li, Guanghui Wang
This paper, for the first time, reveals the fundamental reason that impedes the scale-up of layer-wise learning is due to the relatively poor separability of the feature space in shallow layers.
no code implementations • 13 Jul 2020 • Wenchi Ma, Kaidong Li, Guanghui Wang
In this paper, we aim at single-shot object detectors and propose a location-aware anchor-based reasoning (LAAR) for the bounding boxes.
no code implementations • 12 Jul 2020 • Krushi Patel, Kaidong Li, Ke Tao, Quan Wang, Ajay Bansal, Amit Rastogi, Guanghui Wang
In this work, we compare the performance of the state-of-the-art general object classification models for polyp classification.
no code implementations • 4 Dec 2019 • Kaidong Li, Wenchi Ma, Usman Sajid, Yuanwei Wu, Guanghui Wang
In this chapter, we present a brief overview of the recent development in object detection using convolutional neural networks (CNN).