For real-world language applications, detecting an out-of-distribution (...
Computer-assisted automatic analysis of diabetic retinopathy (DR) is of ...
While pre-trained language models (PLMs) have become a de-facto standard...
Recently, diabetic retinopathy (DR) screening utilizing ultra-wide optic...
The text retrieval task is mainly performed in two ways: the bi-encoder
...
Purpose: Develop a deep learning-based automated method to segment meibo...
This paper introduces contrastive siamese (c-siam) network, an architect...
Reducing prediction delay for streaming end-to-end ASR models with minim...
In this study, we address the challenges in developing a deep learning-b...
In this paper we present a Transformer-Transducer model architecture and...
Git metadata contains rich information for developers to understand the
...
Although supervised learning based on a deep neural network has recently...
Transformer neural networks (TNN) demonstrated state-of-art performance ...
The Transformer architecture recently replaced recurrent neural networks...
Supervised learning based on a deep neural network recently has achieved...
This paper presents an empirical exploration of the use of capsule netwo...
Despite the remarkable progress achieved on automatic speech recognition...
In this paper, a novel architecture for a deep recurrent neural network,...