The increasingly Large Language Models (LLMs) demonstrate stronger langu...
Novel class discovery (NCD) aims to infer novel categories in an unlabel...
Language identification describes the task of recognizing the language o...
Binary neural networks are the extreme case of network quantization, whi...
Transformer-based architectures like BERT have achieved great success in...
Novel class discovery (NCD) aims to infer novel categories in an unlabel...
Harmful repercussions from sharing sensitive or personal data can hamper...
The challenging field of scene text detection requires complex data
anno...
Contrastive Language–Image Pre-training (CLIP) has shown remarkable succ...
One of the most pressing problems in the automated analysis of historica...
Recent works on Binary Neural Networks (BNNs) have made promising progre...
Mutual knowledge distillation (MKD) improves a model by distilling knowl...
The analysis of the compression effects in generative adversarial networ...
Digitized archives contain and preserve the knowledge of generations of
...
Generative Adversarial Networks (GANs) have achieved state-of-the-art
pe...
We propose a family of metrics to assess language generation derived fro...
Objective and interpretable metrics to evaluate current artificial
intel...
Binary Neural Networks (BNNs) are neural networks which use binary weigh...
We propose to tackle the mode collapse problem in generative adversarial...
Over the past few years, several new methods for scene text recognition ...
Sign(ed) languages use gestures, such as hand or head movements, for
com...
Nowadays processing of Big Security Data, such as log messages, is commo...
Binary Neural Networks (BNNs) show promising progress in reducing
comput...
Cloud applications expose - besides service endpoints - also potential o...
We demonstrate that effortlessly accessible digital records of behavior ...
Convolutional neural networks have achieved astonishing results in diffe...
We propose a new generative adversarial architecture to mitigate imbalan...
Recently, deep neural networks have achieved remarkable performance on t...
We propose a new generative adversarial architecture to mitigate imbalan...
Convolutional neural networks have achieved astonishing results in diffe...
We propose to incorporate adversarial dropout in generative multi-advers...
The ubiquitous application of emerging blockchain technology in numerous...
This paper provides an overview of the Self-Sovereign Identity (SSI) con...
Detecting and recognizing text in natural scene images is a challenging,...
Detecting and recognizing text in natural scene images is a challenging,...
Binary Neural Networks (BNNs) can drastically reduce memory size and acc...
This work presents an end-to-end trainable deep bidirectional LSTM
(Long...