Results 31 to 40 of about 157,621 (267)
Breaking CAPTCHA with Capsule Networks
Neural Networks, 2022 Convolutional Neural Networks have achieved state-of-the-art performance in image classification. Their lack of ability to recognise the spatial relationship between features, however, leads to misclassification of the variants of the same image. Capsule Networks were introduced to address this issue by incorporating the spatial information of image ...
Ionela Georgiana Mocanu +2 more
openaire +3 more sources
Remote Sensing, 2021 In order to overcome the disadvantages of convolution neural network (CNN) in the current hyperspectral image (HSI) classification/segmentation methods, such as the inability to recognize the rotation of spatial objects, the difficulty to capture the ...
Le Sun +4 more
doaj +1 more source
Capsule Routing for Sound Event Detection [PDF]
, 2018 The detection of acoustic scenes is a challenging problem in which environmental sound events must be detected from a given audio signal. This includes classifying the events as well as estimating their onset and offset times.
bahdanau +14 more
core +2 more sources
MIRN: A multi-interest retrieval network with sequence-to-interest EM routing.
PLoS ONE, 2023 Vector-based retrieval have been widely adopted to process online users' diverse interests for recommendations. However, most of them utilize a single vector to represent user multiple interests (UMI), inevitably impairing the accuracy and diversity of ...
Xiliang Zhang +5 more
doaj +1 more source
GE: Portuguese Journal of Gastroenterology, 2021 Introduction: Capsule endoscopy has revolutionized the management of patients with obscure gastrointestinal bleeding. Nevertheless, reading capsule endoscopy images is time-consuming and prone to overlooking significant lesions, thus limiting its ...
Miguel Mascarenhas Saraiva +8 more
doaj +1 more source
Pushing the Limits of Capsule Networks
CoRR, 2021 Convolutional neural networks use pooling and other downscaling operations to maintain translational invariance for detection of features, but in their architecture they do not explicitly maintain a representation of the locations of the features relative to each other.
Prem Nair, Rohan Doshi, Stefan Keselj
openaire +2 more sources
Monaural speech separation with deep learning using phase modelling and capsule networks [PDF]
, 2019 The removal of background noise from speech audio is a problem with high practical relevance. A variety of deep learning approaches have been applied to it in recent years, most of which operate on a magnitude spectrogram representation of a noisy ...
dubey +9 more
core +1 more source
Cv-CapsNet: Complex-Valued Capsule Network
IEEE Access, 2019 Capsule network (CapsNet) can recognize the objects by encoding the part-whole relationships in a way similar to our human perceptual system and has already shown its great potential in image classification tasks.
Xinming Cheng +3 more
doaj +1 more source
Offline Signature Identification and Verification Based on Capsule Representations
Cybernetics and Information Technologies, 2020 Offline signature is one of the frequently used biometric traits in daily life and yet skilled forgeries are posing a great challenge for offline signature verification. To differentiate forgeries, a variety of research has been conducted on hand-crafted
Gumusbas Dilara, Yildirim Tulay
doaj +1 more source
Capsule Networks as Generative Models
, 2023 Accepted at the 3rd International Workshop on Active Inference, 19th Sept 2022, Grenoble; This version: added reference, corrected typographical error; final submitted ...
Alex B. Kiefer +3 more
openaire +2 more sources