no code implementations • 10 Nov 2022 • Oluwarotimi Williams Samuel, Mojisola Grace Asogbon, Rami Khushaba, Frank Kulwa, Guanglin Li
Surface electromyogram (sEMG) is arguably the most sought-after physiological signal with a broad spectrum of biomedical applications, especially in miniaturized rehabilitation robots such as multifunctional prostheses.
no code implementations • 13 Sep 2022 • Frank Kulwa, Oluwarotimi Williams Samuel, Mojisola Grace Asogbon, Olumide Olayinka Obe, Guanglin Li
Findings from this study suggest that a combination of 75% overlap in 2D EMG signals and wider network kernels may provide ideal motor intents classification for adequate EMG-CNN based prostheses control scheme.
no code implementations • 31 Aug 2022 • Frank Kulwa, Chen Li, Marcin Grzegorzek, Md Mamunur Rahaman, Kimiaki Shirahama, Sergey Kosov
The use of PDLFs enables the network to focus more on the foreground (EMs) by concatenating the pairwise deep learning features of each image to different blocks of the base model SegNet.
no code implementations • 24 Feb 2021 • Md Mamunur Rahaman, Chen Li, YuDong Yao, Frank Kulwa, Xiangchen Wu, Xiaoyan Li, Qian Wang
Pap smear test is a widely performed screening technique for early detection of cervical cancer, whereas this manual screening method suffers from high false-positive results because of human errors.
no code implementations • 24 Feb 2021 • Frank Kulwa, Chen Li, Jinghua Zhang, Kimiaki Shirahama, Sergey Kosov, Xin Zhao, Hongzan Sun, Tao Jiang, Marcin Grzegorzek
In order to fasten, low the cost, increase consistency and accuracy of identification, we propose the novel pairwise deep learning features to analyze microorganisms.
no code implementations • 20 Feb 2021 • Zihan Li, Chen Li, YuDong Yao, Jinghua Zhang, Md Mamunur Rahaman, Hao Xu, Frank Kulwa, Bolin Lu, Xuemin Zhu, Tao Jiang
EMDS-5 can realize to evaluate image preprocessing, image segmentation, feature extraction, image classification and image retrieval functions.
no code implementations • 8 Mar 2020 • Jinghua Zhang, Chen Li, Frank Kulwa, Xin Zhao, Changhao Sun, Zihan Li, Tao Jiang, Hong Li
In order to assist researchers to identify Environmental Microorganisms (EMs) effectively, a Multi-scale CNN-CRF (MSCC) framework for the EM image segmentation is proposed in this paper.
no code implementations • 3 Mar 2020 • Changhao Sun, Chen Li, Jinghua Zhang, Muhammad Rahaman, Shiliang Ai, Hao Chen, Frank Kulwa, Yixin Li, Xiaoyan Li, Tao Jiang
This HCRF model is built up with higher order potentials, including pixel-level and patch-level potentials, and graph-based post-processing is applied to further improve its segmentation performance.