[HTML][HTML] Multi-camera multi-object tracking: a review of current trends and future advances
The nascent applicability of multi-camera tracking (MCT) in numerous real-world
applications makes it a significant computer vision problem. While visual tracking of objects …
applications makes it a significant computer vision problem. While visual tracking of objects …
An industrial network intrusion detection algorithm based on multifeature data clustering optimization model
Industrial networks are complex and diverse. Among existing intrusion prevention systems
available, several of them have problems such as low detection accuracy rate, high false …
available, several of them have problems such as low detection accuracy rate, high false …
Deep learning based multi-channel intelligent attack detection for data security
Deep learning methods, eg, convolutional neural networks (CNNs) and Recurrent Neural
Networks (RNNs), have achieved great success in image processing and natural language …
Networks (RNNs), have achieved great success in image processing and natural language …
Modality-correlation-aware sparse representation for RGB-infrared object tracking
To intelligently analyze and understand video content, a key step is to accurately perceive
the motion of the interested objects in videos. To this end, the task of object tracking, which …
the motion of the interested objects in videos. To this end, the task of object tracking, which …
Fast semantic segmentation for scene perception
X Zhang, Z Chen, QMJ Wu, L Cai… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Semantic segmentation is a challenging problem in computer vision. Many applications,
such as autonomous driving and robot navigation with urban road scene, need accurate and …
such as autonomous driving and robot navigation with urban road scene, need accurate and …
Robust visual tracking with correlation filters and metric learning
Discriminative correlation filters (DCFs) have been widely used in the visual tracking
community in recent years. The DCFs-based trackers determine the target location through a …
community in recent years. The DCFs-based trackers determine the target location through a …
Learning attribute-specific representations for visual tracking
In recent years, convolutional neural networks (CNNs) have achieved great success in
visual tracking. Most of existing methods train or fine-tune a binary classifier to distinguish …
visual tracking. Most of existing methods train or fine-tune a binary classifier to distinguish …
RGB-D human matting: A real-world benchmark dataset and a baseline method
The last decade has witnessed an increasing exploration and development of human
matting. However, existing matting works primarily focus on predicting better alpha mattes …
matting. However, existing matting works primarily focus on predicting better alpha mattes …
Plant identification based on very deep convolutional neural networks
Plant identification is a critical step in protecting plant diversity. However, many existing
identification systems prohibitively rely on hand-crafted features for plant species …
identification systems prohibitively rely on hand-crafted features for plant species …
Robust visual tracking via scale-and-state-awareness
Convolutional neural networks (CNNs) have been applied to visual tracking with
demonstrated success in recent years. However, the performance of CNN-based trackers …
demonstrated success in recent years. However, the performance of CNN-based trackers …