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Found 12 papers, 2 papers with code
A GAN-Enhanced Deep Learning Framework for Rooftop Detection from Historical Aerial Imagery
Accurate rooftop detection from historical aerial imagery is vital for examining long-term urban development and human settlement patterns.
Classifier Clustering and Feature Alignment for Federated Learning under Distributed Concept Drift
Moreover, to address data heterogeneity, we study the feature alignment under distributed concept drift, and find two factors that are crucial for feature alignment: the conditional distribution $P(Y|X)$ and the degree of data heterogeneity.
Seed-ASR: Understanding Diverse Speech and Contexts with LLM-based Speech Recognition
Modern automatic speech recognition (ASR) model is required to accurately transcribe diverse speech signals (from different domains, languages, accents, etc) given the specific contextual information in various application scenarios.
Ranked #2 on
Speech Recognition
on AISHELL-1
(using extra training data)
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Deep-learning-based groupwise registration for motion correction of cardiac $T_1$ mapping
In this work, we propose a novel deep-learning-based groupwise registration framework, which omits the need for a template, and registers all baseline images simultaneously.
Improving Large-scale Deep Biasing with Phoneme Features and Text-only Data in Streaming Transducer
Deep biasing for the Transducer can improve the recognition performance of rare words or contextual entities, which is essential in practical applications, especially for streaming Automatic Speech Recognition (ASR).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Text-only Domain Adaptation using Unified Speech-Text Representation in Transducer
Domain adaptation using text-only corpus is challenging in end-to-end(E2E) speech recognition.
HMM-Free Encoder Pre-Training for Streaming RNN Transducer
This work describes an encoder pre-training procedure using frame-wise label to improve the training of streaming recurrent neural network transducer (RNN-T) model.
Deep Convolutional Sparse Coding Network for Pansharpening with Guidance of Side Information
Pansharpening is a fundamental issue in remote sensing field.
FGF-GAN: A Lightweight Generative Adversarial Network for Pansharpening via Fast Guided Filter
In addition, the latent information of features can be preserved effectively through adversarial training.
Utterance-level Permutation Invariant Training with Latency-controlled BLSTM for Single-channel Multi-talker Speech Separation
The experimental results show that uPIT outperforms cPIT when LC-BLSTM is used during inference.
The Domain Shift Problem of Medical Image Segmentation and Vendor-Adaptation by Unet-GAN
In this work, we proposed a generic framework to address this problem, consisting of (1) an unpaired generative adversarial network (GAN) for vendor-adaptation, and (2) a Unet for object segmentation.
An Improved Residual LSTM Architecture for Acoustic Modeling
Long Short-Term Memory (LSTM) is the primary recurrent neural networks architecture for acoustic modeling in automatic speech recognition systems.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
