A novel method for lip movement detection using deep neural network
K Srilakshmi, R Karthik - Journal of Scientific & Industrial …, 2022 - op.niscpr.res.in
… It is the recognition of the speech uttered by individual using visual cues. Visual … best
performance compared to the other deep learning architectures used for the purpose of …
performance compared to the other deep learning architectures used for the purpose of …
Brain tumor analysis using deep learning and VGG-16 ensembling learning approaches
… These limitations stress the importance of the traditional architecture proposed in this work.
… CNNs are deep neural networks, often utilized in deep learning visual depiction analysis [15…
… CNNs are deep neural networks, often utilized in deep learning visual depiction analysis [15…
Machine learning paradigm for structural health monitoring
… deep learning, reinforcement learning, and computer vision (… ’s considerable architectural
scale of neurons and deep layers … in change detection is classification or pattern recognition, …
scale of neurons and deep layers … in change detection is classification or pattern recognition, …
A novel deep-learning model for automatic detection and classification of breast cancer using the transfer-learning technique
… sifying lesions into five classes: mass, calcifications, focal asymmetry, architectural distortion,
or no … is applied to make contrast adjustment so that image anomalies become more visible. …
or no … is applied to make contrast adjustment so that image anomalies become more visible. …
COVID-19 detection and disease progression visualization: Deep learning on chest X-rays for classification and coarse localization
… which can change in extent and appearance over time. If these patterns are … using deep
learning methods. We will derive design insights regarding the dataset and model architecture …
learning methods. We will derive design insights regarding the dataset and model architecture …
Deep learning for visual tracking: A comprehensive survey
SM Marvasti-Zadeh, L Cheng… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
… 2018: Studying different learning & search strategies, and designing more sophisticated
architectures for visual tracking task. 2019: Investigating deep detection & segmentation …
architectures for visual tracking task. 2019: Investigating deep detection & segmentation …
How well do deep learning-based methods for land cover classification and object detection perform on high resolution remote sensing imagery?
… results based on the three deep learning methods visually look much smoother, … deep
learning architectures on high resolution image for land cover classification and object detection …
learning architectures on high resolution image for land cover classification and object detection …
Review on self-supervised image recognition using deep neural networks
… , training a deep learning network from scratch … architecture: The quality of the visual
representations learned using pretext task depends significantly on the type of ConvNet architecture …
representations learned using pretext task depends significantly on the type of ConvNet architecture …
Towards an effective and efficient deep learning model for COVID-19 patterns detection in X-ray images
… which can change in extent and appearance over time. The … Deep learning is a subset of
machine learning in artificial … an efficient convolutional network architecture for detecting any …
machine learning in artificial … an efficient convolutional network architecture for detecting any …
Semantic segmentation using deep learning with vegetation indices for rice lodging identification in multi-date UAV visible images
… segmentation model employing two neural network architectures, FCN-AlexNet, … visible
images are used to calculate three vegetation indicators to improve the applicability of visible …
images are used to calculate three vegetation indicators to improve the applicability of visible …