Due to the development of deep learning networks and big data dimensionality, research on
ensemble deep learning is receiving an increasing amount of attention. This paper takes the …

Continuous resource supply is one of the key points to improve comprehensive national
strength. Resource prediction models supportive of target delineation for successful …

We present BAdaCost, a multi-class cost-sensitive classification algorithm. It combines a set
of cost-sensitive multi-class weak learners to obtain a strong classification rule within the …

Despite the thrilling success achieved by existing binary descriptors, most of them are still in
the mire of three limitations: 1) vulnerable to the geometric transformations; 2) incapable of …

Millions of security cameras were placed in public spaces, generating large quantities of
video data. There is a need to develop smart techniques to identify and classify objects …

In recent years, machine learning algorithms have seen extensive application in chemical
science, especially in cell detection technologies. Machine learning, a branch of artificial …

Constructing accurate training tuples is crucial for unsupervised local descriptor learning, yet
challenging due to the absence of patch labels. The state-of-the-art approach constructs …

In face recognition, searching a person's face in the whole picture is generally too time‐
consuming to ensure high‐detection accuracy. Objects similar to the human face or multi …

Local binary patterns (LBP) has been successfully applied to several tasks in computer
vision due to its efficacy and computational simplicity. LBP can be computed in different …

As one of the key technologies for autonomous driving, traffic sign detection and recognition
(TSDR) remains a challenging task due to the difficulty and complexity of traffic signs …