Semantic Meta-Split Learning: A TinyML Scheme for Few-Shot Wireless Image Classification
Semantic and goal-oriented (SGO) communication is an emerging technology that only transmits significant information for a given task. Semantic communication encounters many challenges, such as computational complexity at end users, availability of data, and privacy-preserving. This work presents a...
Saved in:
| Main Authors: | Eslam Eldeeb, Mohammad Shehab, Hirley Alves, Mohamed-Slim Alouini |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Transactions on Machine Learning in Communications and Networking |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10948463/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
TinyML with Meta-Learning on Microcontrollers for Air Pollution Prediction
by: I Nyoman Kusuma Wardana, et al.
Published: (2024-04-01) -
IoT device for detecting abnormal vibrations in motors using TinyML
by: Stalin Arciniegas, et al.
Published: (2025-04-01) -
A Holistic Review of the TinyML Stack for Predictive Maintenance
by: Emil Njor, et al.
Published: (2024-01-01) -
Empowering voice assistants with TinyML for user-centric innovations and real-world applications
by: Sireesha Chittepu, et al.
Published: (2025-05-01) -
TinyML and IoT-enabled system for automated chicken egg quality analysis and monitoring
by: Omoy Kombe Hélène, et al.
Published: (2025-12-01)