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Journal of King Saud University: Computer and Information Sciences, 2022 Modern day computer vision tasks requires efficient solution to problems such as image recognition, natural language processing, object detection, object segmentation and language translation.
Mensah Kwabena Patrick +3 more
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Residual Vector Capsule: Improving Capsule by Pose Attention
IEEE Access, 2021 The convolutional neural network has significantly improved the accuracy of image recognition; however, it performs in a fragile manner when we apply viewpoint transformation or add noise to the image.
Ning Xie, Xiaoxia Wan
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Quaternion Capsule Networks [PDF]
2020 25th International Conference on Pattern Recognition (ICPR), 2021 Capsules are grouping of neurons that allow to represent sophisticated information of a visual entity such as pose and features. In the view of this property, Capsule Networks outperform CNNs in challenging tasks like object recognition in unseen viewpoints, and this is achieved by learning the transformations between the object and its parts with the ...
Baris Ozcan, Furkan Kinli, Furkan Kirac
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From Auto-encoders to Capsule Networks: A Survey [PDF]
E3S Web of Conferences, 2021 Convolutional Neural Networks are a very powerful Deep Learning algorithm used in image processing, object classification and segmentation. They are very robust in extracting features from data and largely used in several domains.
El Alaoui-Elfels Omaima, Gadi Taoufiq
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IEEE Access, 2021 This work presents an investigation on Improved Extended Kalman Filter (IEKF) performance for induction motor drive without a speed sensor. The performance of a direct sensorless vector-controlled system through simulation and experimental work is tested.
Mohana Lakshmi Jayaramu +5 more
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Simplified Routing Mechanism for Capsule Networks
Algorithms, 2023 Classifying digital images using neural networks is one of the most fundamental tasks within the field of artificial intelligence. For a long time, convolutional neural networks have proven to be the most efficient solution for processing visual data ...
János Hollósi +2 more
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Quantum Science and Technology, 2022 Abstract Capsule networks (CapsNets), which incorporate the paradigms of connectionism and symbolism, have brought fresh insights into artificial intelligence (AI). The capsule, as the building block of CapsNets, is a group of neurons represented by a vector to encode different features of an entity.
Zidu Liu +4 more
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Residual Capsule Network [PDF]
2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), 2019 Convolution Neural Network (CNN) has been the most influential innovations in the filed of Computer Vision. CNN have shown a substantial improvement in the field of Machine Learning. But they do come with their own set of drawbacks - CNN need a large dataset, hyperparameter tuning is nontrivial and importantly, they lose all the internal information ...
Sree Bala Shruthi Bhamidi +1 more
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ICTACT Journal on Image and Video Processing, 2021 The text presented in videos contains important information for a wide range of vision-based applications. The key modules for extracting this information include detection of text followed by its recognition, which are the subject of our study.
Ahmed Tibermacine, Selmi Mohamed Amine
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, 2022 Capsule networks are a class of neural networks that achieved promising results on many computer vision tasks. However, baseline capsule networks have failed to reach state-of-the-art results on more complex datasets due to the high computation and memory requirements.
Gugglberger, Josef +2 more
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