26 papers · ranked by Valyu relevance
Wenhuan Cao, Shucai Huang
By applying compressive sensing to infrared imaging systems, the sampling and transmitting time can be remarkably reduced. Therefore, in order to meet the real-time requirements of infrared small target detection tasks in the remote sensing field, many approaches based on compressive sensing have been proposed.…
Bharat Bohara
Choosing a decision threshold is one of the challenging job in any classification tasks. How much the model is accurate, if the deciding boundary is not picked up carefully, its entire performance would go in vain. On the other hand, for imbalance classification where one of the classes is dominant over another…
Yukai Lin, Qiangfu Zhao, Giovanni Collodi, Marco Passafiume + 1 more
'Stefano Maddio'] In the current era of advanced IoT technology, human occupancy monitoring and positioning technology is widely used in various scenarios. For example, it can optimize passenger flow in public transportation systems, enhance safety in large shopping malls, and adjust smart home devices based on the…
M. Sumathi, T. Balaji
- Remote sensing image classification can be performed in many different ways to extract meaningful features. One common approach is to perform edge detection. A second approach is to try and detect whole shapes, given the fact that these shapes usually tend to have distinctive properties such as object foreground or…
Handuo Zhang, Jun Na, Bin Zhang, Claudia Campolo
With the development of intelligent IoT applications, vast amounts of data are generated by various volume sensors. These sensor data need to be reduced at the sensor and then reconstructed later to save bandwidth and energy. As the reduced data increase, the reconstructed data become less accurate. Usually, the…
Miao Zhang, Guo Wei, Hua Wang
Electrocardiogram (ECG) denoising is a biomedical research area of great importance. In this paper, an integrated empirical mode decomposition adaptive threshold denoising method (IEMD-ATD) is proposed for processing ECGs. Three methods are included in the IEMD-ATD. First, an integrated EMD method based on a framework…
Chiara Fioravanti, Christoph Braun, Axel Lindner, Sergio Ruiz + 2 more
Adaptive threshold estimation procedures sample close to a subject’s perceptual threshold by dynamically adapting the stimulation based on the subject’s performance. Yet, perceptual thresholds not only depend on the observers’ sensory capabilities but also on any bias in terms of their expectations and response…
Ananias Pereira Neto, Fabrício J. B. Barros
Introduction Wavelet thresholding techniques are crucial in mitigating noise in data communication and storage systems. In image processing, particularly in medical imaging like MRI, noise reduction is vital for improving visual quality and accurate analysis. While existing methods offer noise reduction, they often…
Erik Alan Petersen, Yi Shen
The Auditory Brainstem Response (ABR) can be used to evaluate hearing sensitivity of animals who are unable to respond to behavioral tasks. However, typical data collection methods are time consuming; decreasing the measurement time may save resources or allow researchers to spend more time on other tasks. Here, an…
Lihua Lei, William Fithian
Summary. We consider the problem of multiple hypothesis testing with generic side information: for each hypothesis Hi we observe both a p-value pi and some predictor xi encoding contextual information about the hypothesis. For large-scale problems, adaptively focusing power on the more promising hypotheses (those more…
Yan Hu, Jianfeng Ren, Jianlong Yang, Ruibing Bai + 1 more
Optical coherence tomography (OCT) images is widely used in ophthalmic examination, but their qualities are often affected by noises. Shearlet transform has shown its effectiveness in removing image noises because of its edge-preserving property and directional sensitivity. In the paper, we propose an adaptive…
Robert A. Bridges, Jessie D. Jamieson, Joel W. Reed
—Anomaly detection (AD) has garnered ample attention in security research, as such algorithms complement existing signature-based methods but promise detection of never-before-seen attacks. Cyber operations now manage a high volume of heterogeneous log data; hence, AD in such operations involves multiple (e.g., per IP…
Fangfang Hong, Ruby Bouhassira, Jason Chow, Craig Sanders + 4 more
Color discrimination thresholds—the smallest detectable color differences—provide a benchmark for models of color vision, enable quantitative evaluation of eye diseases, and inform the design of display technologies. Despite their importance, a comprehensive characterization of these thresholds has long been considered…
Fangfang Hong, Ruby Bouhassira, Jason Chow, Craig Sanders + 4 more
Discrimination thresholds reveal the limits of human perception; scientists have studied them since the time of Fechner in the 1800s. Forced-choice psychophysical methods combined with the method of constant stimuli or parametric adaptive trial-placement procedures are well-suited for measuring one-dimensional…
Hongda Shen, Eren Kurshan
Machine learning models have widely been used in fraud detection systems. Most of the research and development efforts have been concentrated on improving the performance of the fraud scoring models. Yet, the downstream fraud alert systems still have limited to no model adoption and rely on manual steps. Alert systems…
Xue Yang, Enda Howley, Micheal Schukat
The complexity and scale of IT systems are increasing dramatically, posing many challenges to real-world anomaly detection. Deep learning anomaly detection has emerged, aiming at feature learning and anomaly scoring, which has gained tremendous success. However, little work has been done on the thresholding problem…
Peter K. Kimani, Susan Todd, Lindsay A. Renfro, Nigel Stallard
Recently, several study designs incorporating treatment effect assessment in biomarker-based subpopulations have been proposed. Most statistical methodologies for such designs focus on the control of type I error rate and power. In this paper, we have developed point estimators for clinical trials that use the…
Yusuf Ozuysal, David B. Kastner, Stephen A. Baccus
To transmit information efficiently in a changing environment, the retina adapts to visual contrast by adjusting its gain, latency and mean response. Additionally, the temporal frequency selectivity, or bandwidth changes to encode the absolute intensity when the stimulus environment is noisy, and intensity differences…
Farshad Kheiri, Shadrokh Samavi, Nader Karimi
Two critical steps in fingerprint recognition are binarization and thinning of the image. The need for real time processing motivates us to select local adaptive thresholding approach for the binarization step. We introduce a new hardware for this purpose based on pipeline architecture. We propose a formula for…
Mike D. Rinderknecht, Raffaele Ranzani, Werner L. Popp, Olivier Lambercy + 1 more
Psychophysical procedures are applied in various fields to assess sensory thresholds. During experiments, sampled psychometric functions are usually assumed to be stationary. However, perception can be altered, for example by loss of attention to the presentation of stimuli, leading to biased data which results in poor…
Olivera Karanovic, Michel Thabet, Hugh R Wilson, Frances Wilkinson
Aims: Flickering light is strongly aversive to many individuals with migraine. This study was designed to evaluate other abnormalities in the processing of temporally modulating visual stimulation. Methods: We measured psychophysical thresholds for detection of a flickering target and for the discrimination of…
Authors not listed
Graph Neural Networks (GNNs) are powerful tools for molecular property prediction, but they are not magic. When applied to molecules unlike their training data, they produce unreliable predictions that are difficult to detect. The Applicability Domain (AD) concept addresses this by defining regions of chemical space…
Finlay Clark, Graeme Robb, Daniel Cole, Julien Michel
Alchemical absolute binding free energy (ABFE) calculations have substantial potential in drug discovery, but are often prohibitively computationally expensive. To unlock their potential, efficient automated ABFE workflows are required to reduce both computational cost and human intervention. We present a…
Shiyue Yang, Graeme Day
We describe the implementation of the Monte Carlo threshold algorithm for molecular crystals as a method to provide an estimate of the energy barriers separating crystal structures. By sampling the local energy minima accessible from multiple starting structures, the simulations yield a global picture of the crystal…
Authors not listed
For applications in gas sensing, purification, and capture, we often wish to search a large set of metal-organic frameworks (MOFs) for the top-K in terms of their Henry coefficient of an adsorbate. A molecular simulation to predict the Henry coefficient of a MOF constitutes a Monte Carlo integration where each sample…
Authors not listed
This study presents a validation and refinement of the “yellow cards” error detection workflow that can be applied to any property connected to molecular structure. In our implementation the workflow employed 5 predictive models with each assigning a “yellow card” to 5% of the entries with worst prediction accuracy.…