Object detection is a fundamental visual recognition problem in computer vision and has
been widely studied in the past decades. Visual object detection aims to find objects of …

Data augmentation is vital for deep learning neural networks. By providing massive training
samples, it helps to improve the generalization ability of the model. Weakly supervised …

Performing data augmentation for learning deep neural networks is well known to be
important for training visual recognition systems. By artificially increasing the number of …

Performing data augmentation for learning deep neural networks is known to be important
for training visual recognition systems. By artificially increasing the number of training …

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 …

The area, object detection has seen a drastic development of algorithms and techniques
over the past years. The arrival of deep learning has boosted the improvement in accuracy …

Object detection is a pivotal task for many unmanned aerial vehicle (UAV) applications.
Compared to general scenes, the objects in aerial images are typically much smaller. For …

Vehicle detection is a challenging problem in autonomous driving systems, due to its large
structural and appearance variations. In this paper, we propose a novel vehicle detection …

The growing amounts of online multimedia content challenge the current search,
recommendation and information retrieval systems. Information in the form of visual …

Aiming at the problems of electrical connector defect detection, such as low automation, low
detection accuracy, slow detection speed, and poor robustness, an improved Yolo v3 …