Muhammad Anwar Ma'sum

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Research activity per year

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

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Dive into the research topics where Muhammad Anwar Ma'sum is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

1 Similar Profiles

2 Finished

Meta Deep Metric Learning for Low Labeled Biomedical Data
Ma'sum, M. A. (PI)
1/01/22 → 31/12/22
Project: Research
Developing Meta Deep Learning Algorithm for Few Short Video Segmentation from Disaster Surveillance Data
Ma'sum, M. A. (PI)
1/01/22 → 31/12/22
Project: Research

42 Conference contribution
12 Article
3 Paper
2 Copyright

Cross-domain few-shot learning via adaptive transformer networks
Paeedeh, N., Pratama, M., Ma'sum, M. A., Mayer, W., Cao, Z. & Kowlczyk, R., 15 Mar 2024, In: Knowledge-Based Systems. 288, 111458.
Research output: Contribution to journal › Article › peer-review

Open Access
2 Citations (Scopus)
Dynamic Long-Term Time-Series Forecasting via Meta Transformer Networks
Ma'sum, M. A., Sarkar, R., Pratama, M., Ramasamy, S., Anavatti, S., Liu, L., Habibullah & Kowalczyk, R., 2024, (Accepted/In press) In: IEEE Transactions on Artificial Intelligence. 5, 8, p. 1-11 11 p.
Research output: Contribution to journal › Article › peer-review
Few-Shot Continual Learning via Flat-to-Wide Approaches
Ma'sum, M. A., Pratama, M., Lughofer, E., Liu, L., Habibullah & Kowalczyk, R., 2024, (Accepted/In press) In: IEEE Transactions on Neural Networks and Learning Systems. p. 1-13 13 p.
Research output: Contribution to journal › Article › peer-review

Open Access
PIP: Prototypes-Injected Prompt for Federated Class Incremental Learning
Ma'sum, M. A., Pratama, M., Ramasamy, S., Liu, L., Habibullah, H. & Kowalczyk, R., 21 Oct 2024, CIKM 2024 - Proceedings of the 33rd ACM International Conference on Information and Knowledge Management. Association for Computing Machinery, p. 1670-1679 10 p. (International Conference on Information and Knowledge Management, Proceedings).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Open Access
Assessor-guided learning for continual environments.
Ma'sum, M. A., Pratama, M., Lughofer, E., Ding, W. & Jatmiko, W., 2023, In: Inf. Sci.. 640, 1 p., 119088.
Research output: Contribution to journal › Article › peer-review

11 Citations (Scopus)

Muhammad Anwar Ma'sum

Personal profile

Expertise related to UN Sustainable Development Goals

Fingerprint

Collaborations and top research areas from the last five years

Dive into details

Meta Deep Metric Learning for Low Labeled Biomedical Data

Developing Meta Deep Learning Algorithm for Few Short Video Segmentation from Disaster Surveillance Data

Cross-domain few-shot learning via adaptive transformer networks

Dynamic Long-Term Time-Series Forecasting via Meta Transformer Networks

Few-Shot Continual Learning via Flat-to-Wide Approaches

PIP: Prototypes-Injected Prompt for Federated Class Incremental Learning

Assessor-guided learning for continual environments.

Muhammad Anwar Ma'sum

Personal profile

Expertise related to UN Sustainable Development Goals

Fingerprint

Collaborations and top research areas from the last five years

Projects

Meta Deep Metric Learning for Low Labeled Biomedical Data

Developing Meta Deep Learning Algorithm for Few Short Video Segmentation from Disaster Surveillance Data

Research output

Cross-domain few-shot learning via adaptive transformer networks

Dynamic Long-Term Time-Series Forecasting via Meta Transformer Networks

Few-Shot Continual Learning via Flat-to-Wide Approaches

PIP: Prototypes-Injected Prompt for Federated Class Incremental Learning

Assessor-guided learning for continual environments.