相关论文: The iCanClean Algorithm: How to Remove Artifacts u…

Current methods focusing on medical image segmentation suffer from incorrect annotations, which is known as the noisy label issue. Most medical image segmentation with noisy labels methods utilize either noise transition matrix,…

Audio impairment recognition is based on finding noise in audio files and categorising the impairment type. Recently, significant performance improvement has been obtained thanks to the usage of advanced deep learning models. However,…

Brain-Computer Interface (BCI) is an essential mechanism that interprets the human brain signal. It provides an assistive technology that enables persons with motor disabilities to communicate with the world and also empowers them to lead…

EEG recordings contain rich information about neural activity but are subject to artifacts, noise, and superficial differences due to sensors, amplifiers, and filtering. Independent component analysis and automatic labeling of independent…

Noisy labels can impair the performance of deep neural networks. To tackle this problem, in this paper, we propose a new method for filtering label noise. Unlike most existing methods relying on the posterior probability of a noisy…

In this paper, we study the problem of learning image classification models with label noise. Existing approaches depending on human supervision are generally not scalable as manually identifying correct or incorrect labels is…

Classical verification of quantum learning allows classical clients to reliably leverage quantum computing advantages by interacting with untrusted quantum servers. Yet, current quantum devices available in practice suffers from a variety…

Ultrasound (US) imaging is a fast and non-invasive imaging modality which is widely used for real-time clinical imaging applications without concerning about radiation hazard. Unfortunately, it often suffers from poor visual quality from…

Contaminants such as dust, dirt and moisture adhering to the camera lens can greatly affect the quality and clarity of the resulting image or video. In this paper, we propose a video restoration method to automatically remove these…

This paper proposes a constant false alarm rate (CFAR) target detection algorithm based on the CLEAN concept and truncated statistics to mitigate the non-homogeneity of reference samples caused by sidelobe contamination and other abnormal…

Acoustic Echo Cancellation (AEC) plays a key role in voice interaction. Due to the explicit mathematical principle and intelligent nature to accommodate conditions, adaptive filters with different types of implementations are always used…

Cochlear implant users struggle to understand speech in reverberant environments. To restore speech perception, artifacts dominated by reverberant reflections can be removed from the cochlear implant stimulus. Artifacts can be identified…

Automatically extracted metadata from scholarly documents in PDF formats is usually noisy and heterogeneous, often containing incomplete fields and erroneous values. One common way of cleaning metadata is to use a bibliographic reference…

Noise is an important factor which when get added to an image reduces its quality and appearance. So in order to enhance the image qualities, it has to be removed with preserving the textural information and structural features of image.…

Introduction: Electroencephalogram (EEG) signals have gained significant popularity in various applications due to their rich information content. However, these signals are prone to contamination from various sources of artifacts, notably…

Tunneling spectroscopy is an important tool for the study of both real-space and momentum-space electronic structure of correlated electron systems. However, such measurements often yield noisy data. Machine learning provides techniques to…

Human electroencephalography (EEG) is a brain monitoring modality that senses cortical neuroelectrophysiological activity in high-temporal resolution. One of the greatest challenges posed in applications of EEG is the unstable signal…

Image coding for machines (ICM) aims at reducing the bitrate required to represent an image while minimizing the drop in machine vision analysis accuracy. In many use cases, such as surveillance, it is also important that the visual quality…

A noise map facilitates the monitoring of environmental noise pollution in urban areas. However, state-of-the-art techniques for rendering noise maps in urban areas are expensive and rarely updated, as they rely on population and traffic…

Power line interference may severely corrupt neural recordings at 50/60 Hz and harmonic frequencies. In this paper, we present a robust and computationally efficient algorithm for removing power line interference from neural recordings. The…