In pattern recognition, object recognition is an important research domain due to major
applications such as autonomous driving, robotics, and visual surveillance. Many computer …

Nature-inspired metaheuristics have been extensively investigated to solve challenging
optimization problems. Particle Swarm Optimization (PSO) is one of the most famous nature …

Seabed sediment mapping with acoustical data and ground-truth samples is a growing field
in marine science. In recent years, multi-classifier ensemble models have gained …

Knowing the potential students who will fail the final exam at early stages is very challenging
but important for the decision-makers in the educational institutions to take proper actions to …

In this paper, a multi-objective integrated trajectory planning method based on an improved
butterfly optimization algorithm (IBOA) is proposed, to improve the dynamic performance of …

Multi-objective task graph scheduling is a well-known NP-hard problem that plays a
significant role in heterogeneous distributed systems. The solution to the problem is …

The multi-objective grasshopper optimization algorithm (MOGOA) is a relatively new
algorithm inspired by the collective behavior of grasshoppers, which aims to solve multi …

Feature selection (FS), sometimes called variable selection, is an important preprocessing
step for several data mining applications. FS is characterized by the process of selecting …

Abstract A Completely Automated Public Turing Test to tell Computers and Humans Apart
(CAPTCHA) is used in web systems to secure authentication purposes; it may break using …

Secure inference of deep convolutional neural networks (CNNs) under RNS-CKKS involves
polynomial approximation of unsupported non-linear activation functions. However, existing …