Object Detection Network Based on Feature Fusion and Attention Mechanism

Anomaly-based Web Attack Detection: The Application of Deep Neural Network Seq2Seq With Attention Mechanism

Today, the use of the Internet and Internet sites has been an integrated part of the people’s lives, and most activities and important data are in the Internet websites. Thus, attempts to intrude into these websites have grown exponentially. Intrusion detection systems (IDS) of web attacks are an approach to protect users. But, these systems are suffering from such drawbacks as low accuracy in ...

Feature-Level based Video Fusion for Object Detection

Fusion of three-dimensional data from multiple sensors gained momentum, especially in applications pertaining to surveillance, when promising results were obtained in moving object detection. Several approaches to video fusion of visual and infrared data have been proposed in recent literature. They mainly comprise of pixel based methodologies. Surveillance is a major application of video fusio...

Attention-based Object Detection

Feature Sharing between Object Detection and Top-down Attention

Visual search and other attentionally demanding processes are guided from the top down when a specific task is given (e.g., Wolfe et al. 2004). In the simplified stimuli commonly used in visual search experiments, e.g., red and horizontal bars, the selection of potential features that might be biased for is obvious (by design). In a natural setting with real-world objects, the selection of thes...

Generic Object Recognition based on Feature fusion in robot perception

A new generic object recognition (GOR) method for robot perception is proposed in this paper, based on multi-feature fusion of two-dimensional (2D) and 3D scale invariant feature transform descriptors drawn from 2D images and 3D point clouds. The trained support vector machine is utilized to construct multi-category classifiers that recognize the objects. According to our results, this new GOR ...