Two existing double-difference (DD) methods, using either a 3rdSensor or Radiative Transfer Modeling (RTM) as a transfer, are applicable primarily for limited regions and channels, and, thus critical in capturing inter-sensor calibration radiometric Safety Catch bias features.A supplementary method is also desirable for estimating inter-sensor cali

Federated learning is a newly emerged distributed machine learning paradigm, where the clients are allowed to individually train local deep neural network (DNN) models with local data and then jointly aggregate a global DNN model at the central server.Vehicular edge computing (VEC) aims at exploiting the computation and communication resources at t

Cross-media communication underpins many vital applications, especially in underwater resource exploration and the biological population monitoring domains.Water surface micro-amplitude wave (WSAW) frequency detection is the key to cross-media communication, where the WSAW frequency Table can invert the underwater sound source frequency.However, ex

A non-iterative learning algorithm for artificial neural networks is an alternative to optimize the neural network parameters with extremely fast convergence time.Extreme learning machine (ELM) is one of the fastest learning algorithms based on a non-iterative method for a single hidden layer feedforward neural network (SLFN) model.ELM uses a rando