Titlebook: Artificial Intelligence and Soft Computing; 19th International C Leszek Rutkowski,Rafa? Scherer,Jacek M. Zurada Conference proceedings 2020

胰臟

DEI

Method of Real Time Calculation of Learning Rate Value to Improve Convergence of Neural Network Trairparameters, which helps to increase a convergence rate of a training process. There are known techniques of time-based decay, step decay and exponential decay, in which the learning rate is initialized manually and then corrected downwards proportionally to some value. In contrast, in this paper, i

羽毛長(zhǎng)成

Application of an Improved Focal Loss in Vehicle Detections in object detection. Deep neural network object detectors can be grouped in two broad categories: the two-stage detector and the one-stage detector. One-stage detectors are faster than two-stage detectors. However, they suffer from a severe foreground-backg-round class imbalance during training th

bromide

Concept Drift Detection Using Autoencoders in Data Streams Processingrift detector. The autoencoders are neural networks that are learned how to reconstruct input data. As a side effect, they are able to learn compact nonlinear codes, which summarize the most important features of input data. We suspect that the properly learned autoencoder on one part of the data st

thalamus

SLAY

On the Similarity Between Neural Network and Evolutionary AlgorithmBoth classes of algorithms have their history, principles and represent two different biological areas, converted to computer technology. Despite fact that scientists already exhibited that both systems exhibit almost the same behavior dynamics (chaotic regimes etc.), researchers still take both cla

Resign

3D Convolutional Neural Networks for Ultrasound-Based Silent Speech Interfacestongue. Currently, deep neural networks are the most successful technology for this task. The efficient solution requires methods that do not simply process single images, but are able to extract the tongue movement information from a sequence of video frames. One option for this is to apply recurre

frivolous

Deject

6D Pose Estimation of Texture-Less Objects on RGB Images Using CNNsned two neural networks to achieve reliable 6D object pose estimation on such images. The first neural network detects fiducial points of objects, which are then fed to a PnP algorithm responsible for pose estimation. The second one is an rotation regression network delivering at the output the quat

虛構(gòu)的東西

Application of Neural Networks and Graphical Representations for Musical Genre Classificationraphical representations: chromograms and spectrograms. We have used a large dataset of music divided into eight genres, with certain overlapping musical features. Key, style-defining elements and the overall character of specific genres are represented in our proposed visual representation and reco