Recent advances in convolutional neural networks

J Gu, Z Wang, J Kuen, L Ma, A Shahroudy, B Shuai… - Pattern recognition, 2018 - Elsevier
In the last few years, deep learning has led to very good performance on a variety of
problems, such as visual recognition, speech recognition and natural language processing …

Convolutional neural networks-an extensive arena of deep learning. A comprehensive study

N Singh, H Sabrol - Archives of Computational Methods in Engineering, 2021 - Springer
Deep learning is an evolving expanse of machine learning. Machine learning is observing
its neoteric span as deep learning is steadily becoming the pioneer in this field. With the …

Real-time part-based visual tracking via adaptive correlation filters

T Liu, G Wang, Q Yang - Proceedings of the IEEE …, 2015 - openaccess.thecvf.com
Robust object tracking is a challenging task in computer vision. To better solve the partial
occlusion issue, part-based methods are widely used in visual object trackers. However, due …

Occlusion-aware real-time object tracking

X Dong, J Shen, D Yu, W Wang, J Liu… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
The online learning methods are popular for visual tracking because of their robust
performance for most video sequences. However, the drifting problem caused by noisy …

Video tracking using learned hierarchical features

L Wang, T Liu, G Wang, KL Chan… - IEEE Transactions on …, 2015 - ieeexplore.ieee.org
In this paper, we propose an approach to learn hierarchical features for visual object
tracking. First, we offline learn features robust to diverse motion patterns from auxiliary video …

Rapid and non-destructive seed viability prediction using near-infrared hyperspectral imaging coupled with a deep learning approach

T Ma, S Tsuchikawa, T Inagaki - Computers and Electronics in Agriculture, 2020 - Elsevier
Seeds are the basis of the agricultural food industry, greater insights into seed viability
before sowing could improve storage management and field performance. In the present …

Embedding metric learning into an extreme learning machine for scene recognition

C Wang, G Peng, B De Baets - Expert Systems with Applications, 2022 - Elsevier
Metric learning can be very useful to improve the performance of a distance-dependent
classifier. However, separating metric learning from the classifier learning possibly …

Learning to segment with image-level annotations

Y Wei, X Liang, Y Chen, Z Jie, Y Xiao, Y Zhao, S Yan - Pattern Recognition, 2016 - Elsevier
Recently, deep convolutional neural networks (DCNNs) have significantly promoted the
development of semantic image segmentation. However, previous works on learning the …

Deep learning algorithms with applications to video analytics for a smart city: A survey

L Wang, D Sng - arXiv preprint arXiv:1512.03131, 2015 - arxiv.org
Deep learning has recently achieved very promising results in a wide range of areas such
as computer vision, speech recognition and natural language processing. It aims to learn …

Long-term wearable electrocardiogram signal monitoring and analysis based on convolutional neural network

L Meng, K Ge, Y Song, D Yang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Wearable devices are increasingly popular for health monitoring via electrocardiograms
(ECGs) as they can portably monitor heart conditions over a long time. However, so far there …