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Geometric Deep Learning on Molecular Representations [article]

Kenneth Atz, Francesca Grisoni, Gisbert Schneider
2021 arXiv   pre-print
Geometric deep learning (GDL), which is based on neural network architectures that incorporate and process symmetry information, has emerged as a recent paradigm in artificial intelligence.  ...  Emphasis is placed on the relevance of the learned molecular features and their complementarity to well-established molecular descriptors.  ...  The grid-and graph-based structures of meshes enable applications of 2D CNNs, geodesic CNNs and GNNs to learn on mesh-based molecular surfaces.  ... 
arXiv:2107.12375v4 fatcat:sgxlqdxiavbinly4s3zthysxbq

Viewpoint Selection for Photographing Architectures [article]

Jingwu He, Linbo Wang, Wenzhe Zhou, Hongjie Zhang, Xiufen Cui, and Yanwen Guo
2017 arXiv   pre-print
Finally, we extract a number of 2D and 3D features for each image based on multiple visual and geometric cues and perform viewpoint recommendation by learning from both 2D and 3D features using a specifically  ...  Unlike previous efforts devoted to photo quality assessment which mainly rely on 2D image features, we show in this paper combining 2D image features extracted from images with 3D geometric features computed  ...  Furthermore, assessment of aesthetic quality is also addressed by deep learning [7] .  ... 
arXiv:1703.01702v1 fatcat:m23wt7ttqjaqxpbjbtbggnella

A survey on deep learning in medical image analysis

Geert Litjens, Thijs Kooi, Babak Ehteshami Bejnordi, Arnaud Arindra Adiyoso Setio, Francesco Ciompi, Mohsen Ghafoorian, Jeroen A.W.M. van der Laak, Bram van Ginneken, Clara I. Sánchez
2017 Medical Image Analysis  
We survey the use of deep learning for image classification, object detection, segmentation, registration, and other tasks and provide concise overviews of studies per application area.  ...  Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images.  ...  Appendix A: Literature selection Pubmed was searched for papers containing "convolutional" OR "deep learning" in any field.  ... 
doi:10.1016/j.media.2017.07.005 pmid:28778026 fatcat:esbj72ftwvbgzh6jgw367k73j4

Patient-specific prediction of SEEG electrode bending for stereotactic neurosurgical planning

Alejandro Granados, Yuxuan Han, Oeslle Lucena, Vejay Vakharia, Roman Rodionov, Sjoerd B. Vos, Anna Miserocchi, Andrew W. McEvoy, John S. Duncan, Rachel Sparks, Sébastien Ourselin
2021 International Journal of Computer Assisted Radiology and Surgery  
Future work will investigate the integration of electrode bending into planning and quality assessment algorithms.  ...  Results mage-based models outperformed features-based models for all groups, and models that predicted $$\mathbf{lu} $$ lu performed better than for $$\hat{\mathbf{eb }}$$ eb ^ .  ...  The aim of this work is to: 1) assess two data-driven approaches for predicting implanted electrode trajectories using a total of 96 handcrafted features or using electrode direction and a 3D image and  ... 
doi:10.1007/s11548-021-02347-8 pmid:33761063 fatcat:zxeyarupbrbcrlov2unodowhme

Deep learning in medical imaging and radiation therapy

Berkman Sahiner, Aria Pezeshk, Lubomir M. Hadjiiski, Xiaosong Wang, Karen Drukker, Kenny H. Cha, Ronald M. Summers, Maryellen L. Giger
2018 Medical Physics (Lancaster)  
The goals of this review paper on deep learning (DL) in medical imaging and radiation therapy are to (a) summarize what has been achieved to date; (b) identify common and unique challenges, and strategies  ...  for dataset expansion, and conclude by summarizing lessons learned, remaining challenges, and future directions.  ...  Combining deep learning with radiomics approaches Before DL was applied to medical imaging, handcrafted features-based approaches were generally used to analyze the images.  ... 
doi:10.1002/mp.13264 pmid:30367497 fatcat:bottst5mvrbkfedbuocbrstcnm

Facial Expression Recognition Using 3D Points Aware Deep Neural Network

Imen Hamrouni Trimech, Ahmed Maalej, Najoua Essoukri Ben Amara
2021 Traitement du signal  
Point cloud-based Deep Neural Networks (DNNs) have gained increasing attention as an insightful solution in the study field of geometric deep learning.  ...  On the other hand, two major challenges remain understudied when it comes to the use of point cloud-based DNNs for 3D facial expression (FE) recognition.  ...  The efficiency of a feature extraction method can only be established posteriori, through the statistical methods of the feature quality assessment.  ... 
doi:10.18280/ts.380209 fatcat:nhofxsbcarheflnbw2425sh3em

Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation and Diagnosis for COVID-19

Feng Shi, Jun Wang, Jun Shi, Ziyan Wu, Qian Wang, Zhenyu Tang, Kelei He, Yinghuan Shi, Dinggang Shen
2020 IEEE Reviews in Biomedical Engineering  
., for disease diagnosis, tracking, and prognosis.  ...  strengthen the power of the imaging tools and help medical specialists.  ...  Segmented regions could be further used to extract handcrafted or self-learned features for diagnosis and other applications.  ... 
doi:10.1109/rbme.2020.2987975 pmid:32305937 fatcat:cjswoasqh5b6hopdkcgceb5ca4

A Comprehensive Review on Handcrafted and Learning-Based Action Representation Approaches for Human Activity Recognition

Allah Sargano, Plamen Angelov, Zulfiqar Habib
2017 Applied Sciences  
Recently, with the emergence and successful deployment of deep learning techniques for image classification, researchers have migrated from traditional handcrafting to deep learning techniques for HAR.  ...  However, handcrafted representation-based approaches are still widely used due to some bottlenecks such as computational complexity of deep learning techniques for activity recognition.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/app7010110 fatcat:4hbcvrnvhfam5kbf44oqdgz2pm

Deep Learning for Monitoring of Human Gait: A Review

Abdullah S Alharthi, Syed U Yunas, Krikor B Ozanyan
2019 IEEE Sensors Journal  
In the light of the discussed character of gait data, this is attributed to the possibility to extract the gait features automatically in deep learning as opposed to the shallow learning from the handcrafted  ...  The established artificial neural network architectures for deep learning are reviewed for each group, and their performance are compared with particular emphasis on the spatiotemporal character of gait  ...  Most of the reported work is based on handcrafted features deep learning is appeared as an improved approach in terms of increased classification accuracy and reduced computational load. Aicha et al.  ... 
doi:10.1109/jsen.2019.2928777 fatcat:seb7vcs77bae7ixbpkajo3ysee

Learning graph convolutional network for blind mesh visual quality assessment

Ilyass Abouelaziz, Aladine Chetouani, Mohammed El Hassouni, Hocine Cherifi, Longin Jan Latecki
2021 IEEE Access  
24 mesh quality assessment.  ...  This representation 186 allows us to take advantage of graph properties to manipulate 187 the mesh itself and conceive a model-based method to assess 188 the visual quality blindly.  ...  For more information, see https://creativecommons.org/licenses/by/4.0/  ... 
doi:10.1109/access.2021.3094663 fatcat:mb5gsbpojbclhcbamepncq36cy

Malignant Melanoma Classification Using Deep Learning: Datasets, Performance Measurements, Challenges and Opportunities

Ahmad Naeem, Muhammad Shoaib Farooq, Adel Khelifi, Adnan Abid
2020 IEEE Access  
[50] provide an improved method for melanoma detection based on the combination of Linear Discriminant Analysis (LDA) and features derived from the Deep Learning approach.  ...  The quality assessment was carried out by the two authors who retrieved the studies. 1) Has the study uses deep learning algorithms for melanoma diagnosis?  ... 
doi:10.1109/access.2020.3001507 fatcat:hmlampsx3zetjphzqg4brun3xm

Advanced local motion patterns for macro and micro facial expression recognition [article]

B. Allaert, IM. Bilasco, C. Djeraba
2018 arXiv   pre-print
Our method outperforms state-of-the-art methods for micro expression recognition and positions itself among top-rank state-of-the-art methods for macro expression recognition.  ...  The first one is the analysis of the face skin temporal elasticity and face deformations during expression. The second one is a unified approach for both macro and micro expression recognition.  ...  José Mennesson and Mr. Zhongfei (Mark) Zhang for their valuable discussions.  ... 
arXiv:1805.01951v1 fatcat:iyrejb42grci7bhz6c3nrunivu

3D modelling of survey scene from images enhanced with a multi-exposure fusion [article]

Kwok-Leung Chan, Liping Li, Arthur Wing-Tak Leung, Ho-Yin Chan
2021 arXiv   pre-print
Besides point measurement, photogrammetry can also create a three-dimensional (3D) model of the scene. Accurate 3D model reconstruction depends on high quality images.  ...  The image is then enhanced, with each pixel generated from the set of transformed image pixels weighted by a function of the local pattern feature and image saturation.  ...  CityU 11202319) and Hong Kong Innovation and Technology Commission and City University of Hong Kong (Project No. 9042823).  ... 
arXiv:2111.05541v1 fatcat:nxvkqbgxofasbhbwsrve7ow57u

Learning Deep Features for Shape Correspondence with Domain Invariance [article]

Praful Agrawal, Ross T. Whitaker, Shireen Y. Elhabian
2021 arXiv   pre-print
Results on anatomical datasets of human scapula, femur, and pelvis bones demonstrate that features learned in supervised fashion show improved performance for correspondence estimation compared to the  ...  This paper proposes an automated feature learning approach, using deep convolutional neural networks to extract correspondence-friendly features from shape ensembles.  ...  Deep Learning for Shape Correspondence Shape matching methods in computer vision and computer graphics represent shapes as 3D meshes, and use point-wise matching to establish correspondence between a pair  ... 
arXiv:2102.10493v1 fatcat:qqjt5txznrfxlbh742h5tuqa5u

Image Based Artificial Intelligence in Wound Assessment: A Systematic Review [article]

D. M. Anisuzzaman
2020 arXiv   pre-print
To this end, we have carried out a systematic review of intelligent image-based data analysis and system developments for wound assessment.  ...  While artificial intelligence (AI) has found wide applications in health-related sciences and technology, AI-based systems remain to be developed clinically and computationally for high-quality wound care  ...  Various algorithms (rule based, machine learning, and deep learning) will be discussed on feature extraction from 2D image and 3D shapes.  ... 
arXiv:2009.07141v1 fatcat:mbe3fopi75cwvao5opyhgquqgq
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