Filtered Multicarrier Waveforms Classification: A Deep Learning-Based Approach

A way to assess both the accuracy (i.e., the ex- pected fraction of alternatives correctly classified) and the confidence of the classification model (i.e., the probability that

Finally, Problems 14 and 15 contain synthetic data generated from two Deterministic Finite State Automata learned using the ALERGIA algorithm [2] on the NLP data sets of Problems 4

Object Detection is a field of Artificial Intelligence associated with Digital Image Processing and Computer Vision, which deals with detecting instances of an object

Abstract. This paper proposes a novel graph based learning approach to classify agricultural datasets, in which both labeled and unlabelled data are applied to

To evaluate our method on the dataset, we used the network shown in Fig.1 and described in section 2, which consists of a band-pass filter, CSP spatial projection,

"Evaluation of a Numerical Modeling Approach based on the Finite Element Method for calculating the Rough Surface Scattering and Emission of a soil layer" IEEE

”Learning and transferring representations for image steganalysis using convolutional neural network”, Y..

Further testing of the attributes of learning objects in a variety of contexts would contribute to our understanding of notions of interoperability, reusability, granularity and