Multi-Classifier Tree With Transient Features for Drift Compensation in Electronic Nose
<p dir="ltr">Long term sensors drift is a challenging problem to solve for instruments like an Electronic Nose System (ENS). These electronic instruments rely on Machine Learning (ML) algorithms for recognizing the sensed odors. The effect of long-term drift influences the performanc...
محفوظ في:
| المؤلف الرئيسي: | Atiq Ur Rehman (8843024) (author) |
|---|---|
| مؤلفون آخرون: | Samir Brahim Belhaouari (9427347) (author), Muhammad Ijaz (677144) (author), Amine Bermak (1895947) (author), Mounir Hamdi (14150652) (author) |
| منشور في: |
2020
|
| الموضوعات: | |
| الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
مواد مشابهة
-
Assessment and Performance Analysis of Machine Learning Techniques for Gas Sensing E-nose Systems
حسب: Mahmood, Lubna Syeda
منشور في: (2021) -
Hydrogen Sulfide (H<sub>2</sub>S) Sensor: A Concept of Physical Versus Virtual Sensing
حسب: Ahmed Alsarraj (16876014)
منشور في: (2021) -
Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques
حسب: Fares, Samar
منشور في: (2024) -
Improvement of Transient Performance in Microgrids: Comprehensive Review on Approaches and Methods for Converter Control and Route of Grid Stability
حسب: Mandarapu Srikanth (17984122)
منشور في: (2023) -
On the Detection of Unauthorized Drones—Techniques and Future Perspectives: A Review
حسب: Muhammad Asif Khan (7367468)
منشور في: (2022)