Recent advances in convolutional neural networks
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 …
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 …
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
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 issue, part-based methods are widely used in visual object trackers. However, due …
Occlusion-aware real-time object tracking
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 …
performance for most video sequences. However, the drifting problem caused by noisy …
Video tracking using learned hierarchical features
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 …
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 …
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 …
classifier. However, separating metric learning from the classifier learning possibly …
Learning to segment with image-level annotations
Recently, deep convolutional neural networks (DCNNs) have significantly promoted the
development of semantic image segmentation. However, previous works on learning 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 …
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 …
(ECGs) as they can portably monitor heart conditions over a long time. However, so far there …