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Muhammad Hamza Asad
Muhammad Hamza Asad
Verified email at uregina.ca
Title
Cited by
Cited by
Year
Weed detection in canola fields using maximum likelihood classification and deep convolutional neural network
MH Asad, A Bais
Information Processing in Agriculture 7 (4), 535-545, 2020
1392020
Graphene Field-Effect Transistors With High Extrinsic and
M Bonmann, M Asad, X Yang, A Generalov, A Vorobiev, L Banszerus, ...
IEEE Electron Device Letters 40 (1), 131-134, 2018
502018
The dependence of the high-frequency performance of graphene field-effect transistors on channel transport properties
M Asad, M Bonmann, X Yang, A Vorobiev, K Jeppson, L Banszerus, ...
IEEE Journal of the Electron Devices Society 8, 457-464, 2020
212020
End to end segmentation of canola field images using dilated U-Net
HS Ullah, MH Asad, A Bais
IEEE Access 9, 59741-59753, 2021
182021
Crop and weed leaf area index mapping using multi-source remote and proximal sensing
MH Asad, A Bais
IEEE Access 8, 138179-138190, 2020
182020
Integrated 10-GHz graphene FET amplifier
A Hamed, M Asad, MD Wei, A Vorobiev, J Stake, R Negra
IEEE Journal of Microwaves 1 (3), 821-826, 2021
142021
Enhanced high-frequency performance of top-gated graphene FETs due to substrate-induced improvements in charge carrier saturation velocity
M Asad, KO Jeppson, A Vorobiev, M Bonmann, J Stake
IEEE Transactions on Electron Devices 68 (2), 899-902, 2021
142021
Does carrier velocity saturation help to enhance f max in graphene field-effect transistors?
PC Feijoo, F Pasadas, M Bonmann, M Asad, X Yang, A Generalov, ...
Nanoscale advances 2 (9), 4179-4186, 2020
112020
Weed density estimation using semantic segmentation
MH Asad, A Bais
Image and Video Technology: PSIVT 2019 International Workshops, Sydney, NSW …, 2020
112020
Weed detection in canola fields using maximum likelihood classification and deep convolutional neural network. Information Processing in Agriculture, 7 (4), 535-545
MH Asad, A Bais
102020
Graphene field-effect transistors for millimeter wave amplifiers
A Vorobiev, M Bonmann, M Asad, X Yang, J Stake, L Banszerus, ...
2019 44th international conference on infrared, millimeter, and terahertz …, 2019
92019
A comprehensive analysis of the effect of graphene-based dielectric for sustainable electric discharge machining of Ti-6Al-4V. Materials (Basel) 14: 23
K Ishfaq, M Asad, S Anwar, CI Pruncu, M Saleh, S Ahmad
82020
Graphene FET on diamond for high-frequency electronics
M Asad, S Majdi, A Vorobiev, K Jeppson, J Isberg, J Stake
IEEE Electron Device Letters 43 (2), 300-303, 2021
72021
Mobility degradation and series resistance in graphene field-effect transistors
K Jeppson, M Asad, J Stake
IEEE Transactions on Electron Devices 68 (6), 3091-3095, 2021
62021
Soil surface texture classification using RGB images acquired under uncontrolled field conditions
E Babalola, MH Asad, A Bais
IEEE Access, 2023
52023
Weed detection in canola fields using maximum likelihood classification and deep convolutional neural network. Inf. Process. Agric.(2019)
MH Asad, A Bais
5
Impact of adjacent dielectrics on the high-frequency performance of graphene field-effect transistors
M Asad
PQDT-Global, 2021
32021
Estimation of Weed Densities for Variable Rate Herbicide Application
MH Asad
Faculty of Graduate Studies and Research, University of Regina, 2019
12019
Mapping Soil Organic Matter under Field Conditions
MH Asad
Authorea Preprints, 2023
2023
Improved Crop and Weed Detection with Diverse Data Ensemble Learning in Agriculture
MH Asad, S Anwar, A Bais
arXiv preprint arXiv:2310.01055, 2023
2023
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