Gait recognition is becoming one of the promising methods for biometric authentication
owing to its self-effacing nature. Contemporary approaches of joint position-based gait …

There Are Continued Efforts to Build on the Performance of Deep Learning (DL) Models in
Various Fields of Application. Developing New DL Models Continues to Open …

When simulating the mechanical behavior of complex materials, the failure behavior is
strongly influenced by the internal structure. To account for such dependence, models at the …

Weather is essential to human life, but it is difficult to forecast due to its diverse nature. We
evaluated and compared the accuracy of two machine learning algorithms, GRU and …

With physics-informed neural networks (PINNs), inverse problems involving differential
equations can be solved despite noise, sparsity, and varying levels of fidelity. The objective …

Future tokamak devices that aim to create conditions relevant to power plant operations
must consider strategies for mitigating damage to plasma facing components in the divertor …

Remote sensing object detection plays a major role in satellite imaging and is required in
various scenarios such as transportation, forestry, and the ocean. Deep learning techniques …

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that affects
social interaction and communication. Early detection of ASD can significantly improve …

Activation functions play a decisive role in determining the capacity of Deep Neural
Networks as they enable neural networks to capture inherent nonlinearities present in data …

This paper presents a selective review of statistical computation methods for massive data
analysis. A huge amount of statistical methods for massive data computation have been …