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GANterpretations
PabloSamuelCastro....
Published date-11/06/2020
Since the introduction of Generative Adversarial Networks (GANs) [Goodfellow et al., 2014] there has been a regular stream of both technical advances (e.g., Arjovsky et al. [2017]) and creative uses …
Deep coastal sea elements forecasting using U-Net based models
JesúsGarcíaFernández, IsmailAlaouiAbdellaoui, SiamakMehrkanoon....
Published date-11/06/2020
WeatherForecasting
Due to the development of deep learning techniques applied to satellite imagery, weather forecasting that uses remote sensing data has also been the subject of major progress. The present paper …
Binary Neural Network Aided CSI Feedback in Massive MIMO System
ZhilinLu, JintaoWang, JianSong....
Published date-11/05/2020
Binarization
In massive multiple-input multiple-output (MIMO) system, channel state information (CSI) is essential for the base station to achieve high performance gain. Recently, deep learning is widely used in CSI compression …
CompressAI: a PyTorch library and evaluation platform for end-to-end compression research
JeanBégaint, FabienRacapé, SimonFeltman....
Published date-11/05/2020
ImageCompression, MS-SSIM, SSIM, VideoCompression
This paper presents CompressAI, a platform that provides custom operations, layers, models and tools to research, develop and evaluate end-to-end image and video compression codecs. In particular, CompressAI includes pre-trained …
Short-Term Memory Optimization in Recurrent Neural Networks by Autoencoder-based Initialization
AntonioCarta, AlessandroSperduti, DavideBacciu....
Published date-11/05/2020
Training RNNs to learn long-term dependencies is difficult due to vanishing gradients. We explore an alternative solution based on explicit memorization using linear autoencoders for sequences, which allows to maximize …
Anomalous Sound Detection as a Simple Binary Classification Problem with Careful Selection of Proxy Outlier Examples
PaulPrimus, VerenaHaunschmid, PatrickPraher....
Published date-11/05/2020
AnomalyDetection
Unsupervised anomalous sound detection is concerned with identifying sounds that deviate from what is defined as 'normal', without explicitly specifying the types of anomalies. A significant obstacle is the diversity …