Y Cui, R Chen, W Chu, L Chen, D Tian… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Autonomous vehicles were experiencing rapid development in the past few years. However, achieving full autonomy is not a trivial task, due to the nature of the complex and dynamic …
C Cao, F Liu, H Tan, D Song, W Shu… - Genomics …, 2018 - academic.oup.com
Advances in biological and medical technologies have been providing us explosive volumes of biological and physiological data, such as medical images …
P Ongsulee - 2017 15th international conference on ICT and …, 2017 - ieeexplore.ieee.org
It is increasingly recognized that artificial intelligence has been touted as a new mobile. Because of the high volume of data that being generated by devices, sensors and social …
D Pan, A Zeng, L Jia, Y Huang, T Frizzell… - Frontiers in …, 2020 - frontiersin.org
Early detection is critical for effective management of Alzheimer's disease (AD) and screening for mild cognitive impairment (MCI) is common practice. Among several deep …
Abstract Cutting edge Deep Learning (DL) techniques have been widely applied to areas like image processing and speech recognition so far. Likewise, some DL work has been …
In recent years, deep artificial neural networks (including recurrent ones) have won numerous contests in pattern recognition and machine learning. This historical survey …
This paper introduces WILDCAT, a deep learning method which jointly aims at aligning image regions for gaining spatial invariance and learning strongly localized features. Our …
Deep networks have achieved excellent performance in learning representation from visual data. However, the supervised deep models like convolutional neural network require large …
Current high-quality object detection approaches use the scheme of salience-based object proposal methods followed by post-classification using deep convolutional features. This …