of procedural code, thereafter with a more modern approach, the research was further extended by adding object oriented features, so that the developed metric could be used not only for procedural code, but also either object oriented codes or in more general meaning for multi-paradigm codes. Th...
For this purpose, we expand on the recently introduced Twinned Residual Auto-Encoders (TRAE) paradigm for single-image super-resolution (SISR) to extend it to the multi-resolution (MR) domain. The main contributions of this work include (i) the architecture of the MR-TRAE model, which ...
Code commenting practices vary across programming languages, depending on the language paradigm, the communities involved, the purpose of the language, and its usage in different domains etc While Java is a general-purpose, statically-typed object- oriented programming language with wide adoption in in...
The multi-genome meta- bolic modeling analyses we performed enabled us to predict functional inter-dependencies and revealed a long-lasting ecological paradigm, a trade-off between competition and cooperation. We also found that puta- tive metabolic interactions are common and con- straint-dependent,...
Relevant for this work, it was shown how tuning the relative influence of the sensor modalities affected the motoric response in a hand-target phase matching in the presence of visuo-proprioceptive conflict35. Perceptual illusions in humans have been also investigated under this paradigm, such as ...
This dual-training paradigm equips LLMs with unparalleled adaptability, rendering them instrumental in the modern landscape of natural language processing. Since initial pre-training of LLMs requires a large amount of hardware support, scholars tend to fine-tune the pre-trained LLMs to adapt to ...
On the other hand, multi-view learning is a machine learning paradigm that has already formulated effective theories and techniques to handle features from several data views simultaneously [14] by diminishing the impact of the curse of dimensionality [15]. In the formulation of our proposal, we...
Recently, with the emergence of fog computing, many studies have been done on the task scheduling problem to adapt cloud based scheduling algorithms to this new paradigm. Ghobaei-Arani et al. [25] described the task scheduling problem for cyber-physical system (CPS) in the context of fog en...
The Embedding&MLP paradigm is used as the base model by most popular model structures [64]. In our base model, the embeddings of terrorist group action sequences and context elements of objects are fed into MLP with an activation function like rectified linear units (ReLU) [71] and then ...
Sparsity-Enhanced Convolutional Decomposition: A Novel Tensor-Based Paradigm for Blind Hyperspectral Unmixing. IEEE Trans. Geosci. Remote Sens. 2022, 60, 1–14. [Google Scholar] [CrossRef] Licciardi, G.A.; Frate, F.D. Pixel Unmixing in Hyperspectral Data by Means of Neural Networks. IEEE ...