Search Results for author:
Found 11 papers, 2 papers with code
BinsFormer: Revisiting Adaptive Bins for Monocular Depth Estimation
Recently, some methods reformulate it as a classification-regression task to boost the model performance, where continuous depth is estimated via a linear combination of predicted probability distributions and discrete bins.
Ranked #20 on
Monocular Depth Estimation
on KITTI Eigen split
(using extra training data)
A CNN-Based Blind Denoising Method for Endoscopic Images
The number of iterations is reduced about 36% by using transfer learning in our DIP process.
Acoustic Word Embedding System for Code-Switching Query-by-example Spoken Term Detection
In this paper, we propose a deep convolutional neural network-based acoustic word embedding system on code-switching query by example spoken term detection.
Mask Detection and Breath Monitoring from Speech: on Data Augmentation, Feature Representation and Modeling
This paper introduces our approaches for the Mask and Breathing Sub-Challenge in the Interspeech COMPARE Challenge 2020.
Training Wake Word Detection with Synthesized Speech Data on Confusion Words
Confusing-words are commonly encountered in real-life keyword spotting applications, which causes severe degradation of performance due to complex spoken terms and various kinds of words that sound similar to the predefined keywords.
TransfoRNN: Capturing the Sequential Information in Self-Attention Representations for Language Modeling
Also, the TransfoRNN model was applied on the LibriSpeech speech recognition task and has shown comparable results with the Transformer models.
Sparsely Overlapped Speech Training in the Time Domain: Joint Learning of Target Speech Separation and Personal VAD Benefits
This paper proposes the weighted SI-SNR loss, together with the joint learning of target speech separation and personal VAD.
Low-Latency Online Speaker Diarization with Graph-Based Label Generation
To ensure the low latency in the online setting, we introduce a variant of AHC, namely chkpt-AHC, to cluster the speakers.
A Probabilistic Model-Based Robust Waveform Design for MIMO Radar Detection
This paper addresses robust waveform design for multiple-input-multiple-output (MIMO) radar detection.
Constant-Modulus Waveform Design for Dual-Function Radar-Communication Systems in the Presence of Clutter
We investigate the constant-modulus (CM) waveform design for dual-function radar communication systems in the presence of clutter. To minimize the interference power and enhance the target acquisition performance, we use the signal-to-interference-plus-noise-ratio as the design metric. In addition, to ensure the quality of the service for each communication user, we enforce a constraint on the synthesis error of every communication signals. An iterative algorithm, which is based on cyclic optimization, Dinkinbach's transform, and alternating direction of method of multipliers, is proposed to tackle the encountered non-convex optimization problem. Simulations illustrate that the CM waveforms synthesized by the proposed algorithm allow to suppress the clutter efficiently and control the synthesis error of communication signals to a low level.
Co-Design for Spectral Coexistence between RIS-aided MIMO Radar and MIMO Communication Systems
Reconfigurable intelligent surface (RIS) refers to a signal reflection surface containing a large number of low-cost passive reflecting elements.
