Search Results for author: Frank Kulwa

Found 8 papers, 0 papers with code

Multiresolution Dual-Polynomial Decomposition Approach for Optimized Characterization of Motor Intent in Myoelectric Control Systems

no code implementations10 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.

Denoising

Analyzing the Impact of Varied Window Hyper-parameters on Deep CNN for sEMG based Motion Intent Classification

no code implementations13 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.

intent-classification Intent Classification

Segmentation of Weakly Visible Environmental Microorganism Images Using Pair-wise Deep Learning Features

no code implementations31 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.

Specificity

DeepCervix: A Deep Learning-based Framework for the Classification of Cervical Cells Using Hybrid Deep Feature Fusion Techniques

no code implementations24 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.

Cell Segmentation Classification +1

A New Pairwise Deep Learning Feature For Environmental Microorganism Image Analysis

no code implementations24 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.

Specificity

A Multi-scale CNN-CRF Framework for Environmental Microorganism Image Segmentation

no code implementations8 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.

Image Segmentation Segmentation +1

Gastric histopathology image segmentation using a hierarchical conditional random field

no code implementations3 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.

Image Segmentation Segmentation +2

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