Staff Profile
د. دیاری عەبدالخالق حەسەن
diyari.hassan@uniq.edu.iq
PhD in Computer Engineering
Dean of Faculty of Engineering & Computer Science
Faculty of Engineering & Computer Science
Biography
Academic links
Google Scholar ResearchGate Google Siteبڵاوکراوەکان
| # | ناونیشان | Link |
|---|
| # | ناونیشان | بینین | |
|---|---|---|---|
| 1 |
Comparison of feature selection methods in Kurdish text classification |
Publication link | بینین |
| 2 |
Polynomial GSVD Beamforming for Two-User Frequency-Selective MIMO Channels |
Publication link | بینین |
| 3 |
Kurdish News Dataset Headlines (KNDH) through multiclass classification Author links open overlay panel |
Publication link | بینین |
| 4 |
Neural Networks for Computing Eigenvalues of Parahermitian Matrices |
Publication link | بینین |
| 5 |
Efficient Eigenvalue Computation of Parahermitian Matrices Using Neural Networks |
Publication link | بینین |
| 6 |
EXPERIMENTAL ANALYSIS OF RSRP AND RSRQ IN DENSE URBAN DEEP INDOOR SCENARIOS |
Publication link | بینین |
| 7 |
DEEP NEURAL NETWORK-BASED APPROACH FOR COMPUTING SINGULAR VALUES OF MATRICES |
Publication link | بینین |
| 8 |
Critical review of the model description in ‘Kurdish handwritten character recognition using deep learning techniques’ |
Publication link | بینین |
| 9 |
Enhanced Category-Feature Association Measure |
Publication link | بینین |
No Results Found
Comparison of feature selection methods in Kurdish text classification
Polynomial GSVD Beamforming for Two-User Frequency-Selective MIMO Channels
Kurdish News Dataset Headlines (KNDH) through multiclass classification Author links open overlay panel
Neural Networks for Computing Eigenvalues of Parahermitian Matrices
Efficient Eigenvalue Computation of Parahermitian Matrices Using Neural Networks
EXPERIMENTAL ANALYSIS OF RSRP AND RSRQ IN DENSE URBAN DEEP INDOOR SCENARIOS
DEEP NEURAL NETWORK-BASED APPROACH FOR COMPUTING SINGULAR VALUES OF MATRICES
Critical review of the model description in ‘Kurdish handwritten character recognition using deep learning techniques’
Enhanced Category-Feature Association Measure
No Results Found