19 publications with the keyword "deep learning"


Y. Y. Wang, A. S.Hamad, K. Palaniappan, T. E.Lever, and F. Bunyak

LARNet-STC: Spatio-temporal orthogonal region selection network for laryngeal closure detection in endoscopy videos

Computers in Biology and Medicine, pgs. 105339, 2022

deep learning, vocal folds, laryngeal endoscopy, laryngeal closure detection, laryngeal adductor reflex

Abstract, Bibtex, PlainText, URL, DOI, Google Scholar
Y. Y. Wang, O. V. Glinskii, F. Bunyak, and K. Palaniappan

Ensemble of Deep Learning Cascades for Segmentation of Blood Vessels in Confocal Microscopy Images

5OTH ANNUAL APPLIED IMAGERY PATTERN RECOGNITION WORKSHOP, 2021

vessel segmentation, confocal microscopy images, deep learning, semantic segmentation

Abstract, Bibtex, PlainText, PDF, Google Scholar
Y. Y. Wang, K. Gao, A. Hamad, B. McCarthy, A. M. Kloepper, T. E. Lever, and F. Bunyak

Multi-Modal and Multi-Scale Oral Diadochokinesis Analysis using Deep Learning

5OTH ANNUAL APPLIED IMAGERY PATTERN RECOGNITION WORKSHOP, 2021

oral diadochokinesis, syllable detection, mouth/jaw motion, deep learning

Abstract, Bibtex, PlainText, PDF, Google Scholar
N. Al-Shakarji, K. Gao, F. Bunyak, H. Aliakbarpour, E. Blasch, P. Narayaran, G. Seetharaman, and K. Palaniappan

Impact of georegistration accuracy on wide area motion imagery object detection and tracking

IEEE International Conference on Information Fusion (FUSION), pgs. 1-8, 2021

deep learning, fusion, wami, object detection, multi-object tracking, dod

Abstract, Bibtex, PlainText, PDF, URL, Google Scholar
#293: J. K. Lewis, I. E. Toubal, H. Chen, V. Sandesera, M. Lomnitz, Z. Hampel-Arias, C. Prasad, and K. Palaniappan

Deepfake Video Detection Based on Spatial, Spectral, and Temporal Inconsistencies Using Multimodal Deep Learning

Applied Imagery Pattern Recognition Workshop (AIPR), pgs. 1-9, 2020

deepfake detection, deep learning, multi-modal, computer vision

Abstract, Bibtex, PlainText, Software, PDF, URL, DOI, Google Scholar
A. S. Hamad, Y. Y. Wang, T. E. Lever, and F. Bunyak

Ensemble of deep cascades for detection of laryngeal adductor reflex events in Endoscopy Videos

IEEE International Conference on Image Processing (ICIP), pgs. 300-304, 2020

deep learning, laryngeal adductor reflex, automated detection, endoscopy video analysis

Abstract, Bibtex, PlainText, DOI, Google Scholar
N. Al-Shakarji, E. Ufuktepe, F. Bunyak, H. Aliakbarpour, G. Seetharaman, and K. Palaniappan

Semi-automatic system for rapid annotation of moving objects in surveillance videos using deep detection and multi-object tracking techniques

IEEE Applied Imagery Pattern Recognition Workshop (AIPR), pgs. 1-6, 2020

ground truth generator, object annotation, deep learning, object detection, tracking

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#296: E. Ufuktepe, V. Ramtekkar, K. Gao, N. Al-Shakarji, J. Fraser, H. AliAkbarpour, G. Seetharaman, and K. Palaniappan

pyTAG: Python-based interactive training data generation for visual tracking algorithms

Proc. SPIE Conf. Geospatial InfoFusion X (Defense + Commercial Sensing), Volume 11398, 2020

ground-truth generation, visual tracking, crowd sourcing, annotation, deep learning

Abstract, Bibtex, PlainText, Software, URL, DOI, Google Scholar
#289: Y. M. Kassim, O. V. Glinskii, V. V. Glinsky, V. H. Huxley, G. Guidoboni, and K. Palaniappan

Deep U-Net Regression and Hand-Crafted Feature Fusion for Accurate Blood Vessel Segmentation

2019 IEEE International Conference on Image Processing (ICIP), pgs. 1445-1449, 2019

semantic vessel segmentation, deep learning, histogram equalization, random forests, u-net

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#288: G. Yolcu, I. Oztel, S. Kazan, C. Oz, K. Palaniappan, T. E. Lever, and F. Bunyak

Facial expression recognition for monitoring neurological disorders based on convolutional neural network

Multimedia Tools and Applications, Volume 78, pgs. 31581-31603, 2019

facial component segmentation, facial expression recognition, convolutional neural network, deep learning

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
Y. Y. Wang, K. Gao, A. M. Kloepper, Y. Zhao, M. Kuruvilla-Dugdale, T. E. Lever, and F. Bunyak

DeepDDK: A deep learning based oral-diadochokinesis analysis software

IEEE EMBS International Conference on Biomedical & Health Informatics (BHI), pgs. 1--4, 2019

diadochokinesis analysis, speech signal analysis, deep learning, event detection, event localization

Abstract, Bibtex, PlainText, URL, DOI, Google Scholar
N. Al-Shakarji, F. Bunyak, H. Aliakbarpour, G. Seetharaman, and K. Palaniappan

Performance evaluation of semantic video compression using multi-cue object detection

IEEE Applied Imagery Pattern Recognition Workshop (AIPR), pgs. 1-8, 2019

deep learning, object detection, data compression, video surveillance, image motion analysis, saliency

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#287: N. Al-Shakarji, F. Bunyak, H. AliAkbarpour, G. Seetharaman, and K. Palaniappan

Multi-cue vehicle detection for semantic video compression in georegistered aerial videos

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pgs. 56-65, 2019

deep learning, object detection, data compression, video surveillance, image motion analysis

Abstract, Bibtex, PlainText, PDF, URL, Google Scholar
#275: Z. A. Oraibi, H. Yousif, A. Hafiane, G. Seetharaman, and K. Palaniappan

Learning Local and Deep Features for Efficient Cell Image Classification Using Random Forests

25th IEEE International Conference on Image Processing (ICIP), pgs. 2446-2450, 2018

feature extraction, random forests, local features, deep learning, image classification

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#257: Y. M. Kassim and K. Palaniappan

Extracting Retinal Vascular Networks Using Deep Learning Architecture

IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2017

deep learning, vessel segmentation, fundoscopy images, patches, convolution neural network

Abstract, Bibtex, PlainText, PDF, URL, Google Scholar
#259: G. Yolcu, I. Oztel, S. Kazan, C. Oz, K. Palaniappan, T. Lever, and F. Bunyak

Deep learning-based facial expression recognition for monitoring neurological disorders

EEE International Conference on Bioinformatics and Biomedicine (BIBM) , pgs. 1652-1657, 2017

convolutional neural networks, deep learning, facial component segmentation, facial expression recognition

Abstract, Bibtex, PlainText, URL, Google Scholar
#255: Y. M. Kassim, V. B. S. Prasath, O. V. Glinskii, V. V. Glinsky, V. H. Huxley, and K. Palaniappan

Microvasculature segmentation of arterioles using deep CNN

IEEE International Conference on Image Processing (ICIP), 2017

deep learning, segmentation, vasculature, biomedical

Abstract, Bibtex, PlainText, URL, Google Scholar
#239: Z. Liang, S. Jaeger, G. Thoma, J. Huang, P. Guo, A. Powell, K. Silamut, I. Ersoy, M. Poostchi, K. Palaniappan, and R. J. Maude

CNN - Based Image Analysis for Malaria Diagnosis

Proc. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2016

deep learning, malaira, cells, classification, biomedical

Abstract, Bibtex, PlainText, Google Scholar
#231: Z. Al-Milaji, I. Ersoy, K. Palaniappan, and F. Bunyak

Hybrid Deep Learning Framework for the Classification of Epithelial and Stromal Tissues in H&E Images

Proc. First International Workshop on Deep Learning for Pattern Recognition (DLPR), 2016

deep learning, histopathology, segmentation

Bibtex, PlainText, URL, Google Scholar