Multimodal image feature detection with ROI-based optimization for image registration
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Real-Time Image Processing"
DOI: 10.1007/s11554-018-0847-z
Abstract: Image registration plays an imperative part of multimodal video analysis system. In video surveillance applications, change in the environmental conditions makes the registration process hard. Use of multiple sensors makes the system more robust to… read more here.
Keywords: image; system; image registration; registration ... See more keywords
High sensitivity and specificity feature detection in liquid chromatography-mass spectrometry data: A deep learning framework.
Sign Up to like & getrecommendations! Published in 2021 at "Talanta"
DOI: 10.1016/j.talanta.2020.121580
Abstract: Feature detection is a crucial pre-processing step for high-resolution liquid chromatography-mass spectrometry (LC-MS) data analysis. Typical practices based on thresholds or rigid mathematical assumptions can cause ineffective performance in detecting low abundance and non-ideal distributed… read more here.
Keywords: detection; mass spectrometry; chromatography mass; liquid chromatography ... See more keywords
Power of mzRAPP-Based Performance Assessments in MS1-Based Nontargeted Feature Detection
Sign Up to like & getrecommendations! Published in 2022 at "Analytical Chemistry"
DOI: 10.1021/acs.analchem.1c05270
Abstract: When performing chromatography-mass spectrometry-based nontargeted metabolomics, or exposomics, one of the key steps in the analysis is to obtain MS1-based feature tables. Inapt parameter settings in feature detection will result in missing or wrong quantitative… read more here.
Keywords: feature; feature detection; based nontargeted; ms1 based ... See more keywords
Targeted Feature Detection for Data-Dependent Shotgun Proteomics
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Proteome Research"
DOI: 10.1021/acs.jproteome.7b00248
Abstract: Label-free quantification of shotgun LC–MS/MS data is the prevailing approach in quantitative proteomics but remains computationally nontrivial. The central data analysis step is the detection of peptide-specific signal patterns, called features. Peptide quantification is facilitated… read more here.
Keywords: detection; feature; approach; quantification ... See more keywords
Explainable GeoAI: can saliency maps help interpret artificial intelligence’s learning process? An empirical study on natural feature detection
Sign Up to like & getrecommendations! Published in 2023 at "International Journal of Geographical Information Science"
DOI: 10.1080/13658816.2023.2191256
Abstract: Abstract Improving the interpretability of geospatial artificial intelligence (GeoAI) models has become critically important to open the ‘black box’ of complex AI models, such as deep learning. This paper compares popular saliency map generation techniques… read more here.
Keywords: saliency; feature detection; artificial intelligence; geoai ... See more keywords
TopFD: A Proteoform Feature Detection Tool for Top–Down Proteomics
Sign Up to like & getrecommendations! Published in 2022 at "Analytical Chemistry"
DOI: 10.1101/2022.10.11.511828
Abstract: Top-down liquid chromatography-mass spectrometry (LC-MS) analyzes intact proteoforms and generates mass spectra containing peaks of proteoforms with various isotopic compositions, charge states, and retention times. An essential step in top-down MS data analysis is proteoform… read more here.
Keywords: tool top; feature; feature detection; proteoform feature ... See more keywords
Feature Detection and Matching With Linear Adjustment and Adaptive Thresholding
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3030183
Abstract: Image feature detection and matching technologies are crucial aspects in machine vision. However it is still facing the dilemma between fast operation for real-time application and robust matching. To address this issue, we propose a… read more here.
Keywords: adjustment; detection matching; image; adaptive thresholding ... See more keywords
Enhancing Facial Feature Detection: Hybrid Active Shape and Active Appearance Model (HASAAM)
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Access"
DOI: 10.1109/access.2024.3505536
Abstract: Face landmarking is a primary goal of many projects that lead to face-preparing activities, like biometric recognition and mental state comprehension. Despite the inherent diversity of faces, the topic has proven to be extremely difficult… read more here.
Keywords: active appearance; feature detection; shape; active shape ... See more keywords
Wind Turbine Fault Diagnosis Based on Cyclostationary Feature Detection From Compressive Samples
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Sensors Journal"
DOI: 10.1109/jsen.2024.3431641
Abstract: Compressive sensing theory, capturing fewer data points without compromising essential information, holds significant promise for high-sampling-rate applications, particularly in wind turbine monitoring. The primary strategy within current compressive sensing fault diagnosis involves designing a dictionary… read more here.
Keywords: feature detection; wind turbine; fault diagnosis; fault ... See more keywords
An Autonomous Feature Detection Method of Slow Small Targets on Sea Surface Based on Contextual Bandit
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2024.3353730
Abstract: Under the background of slow small target detection on sea surface, it is a serious problem that the detection performance of existing feature detection methods decreases when the number of coherent pulses is less. In… read more here.
Keywords: detection; method; slow small; feature detection ... See more keywords
Self-Supervised Feature Detection and 3D Reconstruction for Real-Time Neuroendoscopic Guidance
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Biomedical Engineering"
DOI: 10.1109/tbme.2025.3538683
Abstract: Objective: Transventricular approach to deep-brain targets offers direct visualization but also imparts deformation that challenges accurate neuronavigation. 3D reconstruction and registration of the endoscopic view could provide up-to-date, real-time guidance. We develop and evaluate a… read more here.
Keywords: feature detection; reconstruction; self supervised;