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Electrocardiogram (ECG) is the most frequent and routine diagnostic tool used for monitoring heart electrical signals and evaluating its functionality. The human heart can suffer from a variety of diseases, including cardiac arrhythmias.…

Signal Processing · Electrical Eng. & Systems 2022-09-05 Negin Alamatsaz , Leyla s Tabatabaei , Mohammadreza Yazdchi , Hamidreza Payan , Nima Alamatsaz , Fahimeh Nasimi

Cardiotocography (CTG) is a key element when it comes to monitoring fetal well-being. Obstetricians use it to observe the fetal heart rate (FHR) and the uterine contraction (UC). The goal is to determine how the fetus reacts to the…

Signal Processing · Electrical Eng. & Systems 2022-10-03 Julien Bertieaux , Mohammadhadi Shateri , Fabrice Labeau , Thierry Dutoit

Training object detectors with only image-level annotations is very challenging because the target objects are often surrounded by a large number of background clutters. Many existing approaches tackle this problem through object proposal…

Computer Vision and Pattern Recognition · Computer Science 2017-08-08 Wenhui Jiang , Thuyen Ngo , B. S. Manjunath , Zhicheng Zhao , Fei Su

Accurate automated analysis of electroencephalography (EEG) would largely help clinicians effectively monitor and diagnose patients with various brain diseases. Compared to supervised learning with labelled disease EEG data which can train…

Machine Learning · Computer Science 2022-07-05 Yaojia Zheng , Zhouwu Liu , Rong Mo , Ziyi Chen , Wei-shi Zheng , Ruixuan Wang

This paper presents a novel semantic scene change detection scheme with only weak supervision. A straightforward approach for this task is to train a semantic change detection network directly from a large-scale dataset in an end-to-end…

Computer Vision and Pattern Recognition · Computer Science 2022-09-07 Ken Sakurada , Mikiya Shibuya , Weimin Wang

Arbitrary-shaped text detection is an important and challenging task in computer vision. Most existing methods require heavy data labeling efforts to produce polygon-level text region labels for supervised training. In order to reduce the…

Computer Vision and Pattern Recognition · Computer Science 2020-12-02 Mengbiao Zhao , Wei Feng , Fei Yin , Xu-Yao Zhang , Cheng-Lin Liu

Hierarchical text classification, which aims to classify text documents into a given hierarchy, is an important task in many real-world applications. Recently, deep neural models are gaining increasing popularity for text classification due…

Computation and Language · Computer Science 2019-01-01 Yu Meng , Jiaming Shen , Chao Zhang , Jiawei Han

In the digitization of energy systems, sensors and smart meters are increasingly being used to monitor production, operation and demand. Detection of anomalies based on smart meter data is crucial to identify potential risks and unusual…

Signal Processing · Electrical Eng. & Systems 2022-06-16 Wenjing Dai , Xiufeng Liu , Alfred Heller , Per Sieverts Nielsen

Weakly supervised video anomaly detection aims to detect anomalies and identify abnormal categories with only video-level labels. We propose CPL-VAD, a dual-branch framework with cross pseudo labeling. The binary anomaly detection branch…

Computer Vision and Pattern Recognition · Computer Science 2026-03-16 Dayeon Lee , Donghyeong Kim , Chaewon Park , Sungmin Woo , Sangyoun Lee

Recent Weak Supervision (WS) approaches have had widespread success in easing the bottleneck of labeling training data for machine learning by synthesizing labels from multiple potentially noisy supervision sources. However, proper…

Machine Learning · Computer Science 2021-10-12 Jieyu Zhang , Yue Yu , Yinghao Li , Yujing Wang , Yaming Yang , Mao Yang , Alexander Ratner

Videos are more well-organized curated data sources for visual concept learning than images. Unlike the 2-dimensional images which only involve the spatial information, the additional temporal dimension bridges and synchronizes multiple…

Computer Vision and Pattern Recognition · Computer Science 2022-05-13 Keren Ye , Adriana Kovashka

Weakly supervised learning algorithms are critical for scaling audio event detection to several hundreds of sound categories. Such learning models should not only disambiguate sound events efficiently with minimal class-specific annotation…

Sound · Computer Science 2020-05-05 Anurag Kumar , Vamsi Krishna Ithapu

We propose a weakly-supervised cell tracking method that can train a convolutional neural network (CNN) by using only the annotation of "cell detection" (i.e., the coordinates of cell positions) without association information, in which…

Computer Vision and Pattern Recognition · Computer Science 2020-07-17 Hiroki Tokunaga , Brian Kenji Iwana , Yuki Teramoto , Akihiko Yoshizawa , Ryoma Bise

Medical image annotation is a major hurdle for developing precise and robust machine learning models. Annotation is expensive, time-consuming, and often requires expert knowledge, particularly in the medical field. Here, we suggest using…

Computer Vision and Pattern Recognition · Computer Science 2020-09-28 Holger R Roth , Dong Yang , Ziyue Xu , Xiaosong Wang , Daguang Xu

Anomaly detection or more generally outliers detection is one of the most popular and challenging subject in theoretical and applied machine learning. The main challenge is that in general we have access to very few labeled data or no…

Machine Learning · Computer Science 2023-05-31 Mansour Zoubeirou A Mayaki , Michel Riveill

Audio tagging aims to perform multi-label classification on audio chunks and it is a newly proposed task in the Detection and Classification of Acoustic Scenes and Events 2016 (DCASE 2016) challenge. This task encourages research efforts to…

Sound · Computer Science 2017-03-20 Yong Xu , Qiuqiang Kong , Qiang Huang , Wenwu Wang , Mark D. Plumbley

Tongue diagnosis in Traditional Chinese Medicine (TCM) is a crucial diagnostic method that can reflect an individual's health status. Traditional methods for identifying tooth-marked tongues are subjective and inconsistent because they rely…

Computer Vision and Pattern Recognition · Computer Science 2024-08-30 Yongcun Zhang , Jiajun Xu , Yina He , Shaozi Li , Zhiming Luo , Huangwei Lei

Sleep apnea (SA) is a type of sleep disorder characterized by snoring and chronic sleeplessness, which can lead to serious conditions such as high blood pressure, heart failure, and cardiomyopathy (enlargement of the muscle tissue of the…

Computer Vision and Pattern Recognition · Computer Science 2022-09-13 Anh-Tu Nguyen , Thao Nguyen , Huy-Khiem Le , Huy-Hieu Pham , Cuong Do

We address the problem of sequentially selecting and observing processes from a given set to find the anomalies among them. The decision-maker observes a subset of the processes at any given time instant and obtains a noisy binary indicator…

Machine Learning · Computer Science 2021-12-10 Geethu Joseph , Chen Zhong , M. Cenk Gursoy , Senem Velipasalar , Pramod K. Varshney

Speaker Verification still suffers from the challenge of generalization to novel adverse environments. We leverage on the recent advancements made by deep learning based speech enhancement and propose a feature-domain supervised denoising…

Audio and Speech Processing · Electrical Eng. & Systems 2020-02-18 Saurabh Kataria , Phani Sankar Nidadavolu , Jesús Villalba , Nanxin Chen , Paola García , Najim Dehak
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