Deep Learning-based embeddings are used widely for “dense retrieval” in information retrieval, computer vision, NLP, amongst others, owing to capture diverse types of semantic information. This ...
Abstract: Solving the path planning problem of Autonomous Underwater Vehicles (AUVs) is crucial for reducing energy waste and improving operational efficiency. However, two main challenges hinder ...
The health status of bearings is an essential prerequisite to ensure the safe and stable operation of vehicles. However, the negative impact of covariate shifts among data channels on diagnostic ...
You will never be able to prove every mathematical truth. For me, this incompleteness theorem, discovered by Kurt Gödel, is one of the most incredible results in mathematics. It may not surprise ...
cDepartment of Hematology, Oncology and Radiation Physics, Region Skåne, Lund, Sweden dDepartment of Genetics, Pathology and Molecular Diagnostics, Laboratory Medicine, Region Skåne, Lund, Sweden ...
Abstract: A new density-based clustering algorithm, RNN-DBSCAN, is presented which uses reverse nearest neighbor counts as an estimate of observation density. Clustering is performed using a ...
The detection of smoking behavior is an emerging field faced with challenges in identifying small, frequently occluded objects like cigarette butts using existing deep learning technologies. Such ...
1 School of Computer Science & Technology, Dalian University of Technology, Dalian, China. 2 School of Computer Science & Technology, Xinjiang Normal University, Urumqi, China. Nowadays, crop diseases ...
In supervised learning, a set of input variables, such as blood metabolite or gene expression levels, are used to predict a quantitative response variable like hormone level or a qualitative one such ...
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