Kha Do Minh

Nhà nghiên cứu Hồ sơ 6/10

Đại học Bách khoa Hà Nội · Công nghệ Thông tin

9 công bố · 15 trích dẫn · h-index 2

Thông tin

🏛️Nơi công tác: Đại học Bách khoa Hà Nội
🔬Lĩnh vực: Công nghệ Thông tin
🆔ORCID: 0000-0002-1917-8314
✍️Hồ sơ chưa đầy đủ — bổ sung thông tin

Công bố tiêu biểu

Reconfigurable Intelligent Surfaces: A Hardware-Centric Review of Structures, Implementation, Evaluation, and Integration With UAV and Machine Learning6 trích dẫn
IEEE Access · 2025 · DOI

SCADefender: An Autoencoder-Based Defense for CNN-Based Image Classifiers4 trích dẫn
International Journal of Pattern Recognition and Artificial Intelligence · 2023 · DOI

Combinative-distance-based assessment approach for the evaluation of artificial intelligence cloud platforms using probabilistic linguistic hesitant fuzzy sets2 trích dẫn
Journal of Intelligent & Fuzzy Systems · 2023 · DOI

Improving Diversity and Quality of Adversarial Examples in Adversarial Transformation Network1 trích dẫn
Research Square · 2022 · DOI

A symbolic execution-based method to perform untargeted attack on feed-forward neural networks1 trích dẫn
Automated Software Engineering · 2022 · DOI

Improving diversity and quality of adversarial examples in adversarial transformation network1 trích dẫn
Soft Computing · 2022 · DOI

重み付きCFGと境界値を用いたC/C++ソースコードからのテストデータの生成【JST・京大機械翻訳】
IEEE Conference Proceedings · 2020

Method for Improving Quality of Adversarial Examples
Proceedings of the 14th International Conference on Agents and Artificial Intelligence · 2022 · DOI

A Generator-based Method for Attacking Embedding-based Text Classifiers
2022 RIVF International Conference on Computing and Communication Technologies (RIVF) · 2022 · DOI

Về lĩnh vực Công nghệ Thông tin

2.378học giả

36.643công bố

398.190trích dẫn

3.7h-index trung bình

Hướng nghiên cứu phổ biến trong lĩnh vực:

Topic ModelingNatural Language Processing TechniquesAdvanced Neural Network ApplicationsNetwork Security and Intrusion DetectionMultimodal Machine Learning ApplicationsAdvanced Image and Video Retrieval Techniques

Nơi có nhiều học giả lĩnh vực này nhất: