n this work, we introduce a Denser Feature Network (DenserNet) for visual localization. Our work provides three principal contributions. First, we develop a convolutional neural network (CNN) architecture which aggregates feature maps at different …
Tensor decompositions are becoming increasingly important in processing images and videos. Previous methods, such as ANDECOMP/PARAFAC decomposition (CPD), Tucker decomposition (TKD), or tensor train decomposition (TTD), treat individual modes (or …
Tensor decomposition techniques are becoming increasingly important in processing videos with large sizes and dimensions. Under the framework of CANDECOMP/PARAFAC decomposition (CPD), this work studies low-rank sparse tensor approximations (LRSTAs) …
Aerial imagery has been increasingly adopted in mission-critical tasks, such as traffic surveillance, smart cities,and disaster assistance. However, identifying objects from aerial images faces the following challenges: 1) objects of …
This work proposed a new approach called regression PCA (RegPCA) for statistical machine learning and big data analyses. One of the potential use cases investigated in this work is to separate the moving objects (foreground) from the background …
Categorical variables are nominal variables that classify observations by groups. The treatment of categorical variables in regression is a well-studied yet vital problem, with the most popular solution to perform a one hot encoding. However, …
Intrusion detection is a pivotal step for network protection. Usually, intrusion detection is performed at packet level by using deep packet or state-full protocol inspection to detect malicious requests in the network. However, flow based analyses …