Drone/Bird Classification Based on Features of Tracks Trajectories
This paper presents the outcome of several machine learning techniques used for the task of bird/drone classification based on their tracks. Instead of using static images, the dynamics and features extracted from the trajectories captured in videos are used to provide a more accurate and reliable r...
محفوظ في:
| المؤلف الرئيسي: | Kengeskanov, Maksat (author) |
|---|---|
| مؤلفون آخرون: | Seghrouchni, Amal El Fallah (author), Abu Zitar, Raed (author), Barbaresco, Frederic (author) |
| منشور في: |
2023
|
| الموضوعات: | |
| الوصول للمادة أونلاين: | https://depot.sorbonne.ae/handle/20.500.12458/1407 |
| الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
مواد مشابهة
-
Sliding Window Neural Generated Tracking Based on Measurement Model
حسب: Ejjawi, Haya
منشور في: (2023) -
FPGA-based Parallel Hardware Architecture for Real-time Object Classification
حسب: Qasaimeh, Murad Mohammad
منشور في: (2014) -
Intelligent Hybrid Feature Selection for Textual Sentiment Classification
حسب: Jawad Khan (6422669)
منشور في: (2021) -
Novel Feature Extraction and Classification Technique for Sensor-Based Continuous Arabic Sign Language Recognition
حسب: Tuffaha, Mohammed
منشور في: (2015) -
A Novel Genetic Trajectory Planning Algorithm With Variable Population Size for Multi-UAV-Assisted Mobile Edge Computing System
حسب: Muhammad Asim (2235472)
منشور في: (2021)