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Ibrahem Kandel
Ibrahem Kandel
Center for Cardiovascular Regeneration, Houston Methodist Research Institute, Houston, TX, USA
Email confirmado em houstonmethodist.org
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Citado por
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Ano
The effect of batch size on the generalizability of the convolutional neural networks on a histopathology dataset
I Kandel, M Castelli
ICT express 6 (4), 312-315, 2020
4412020
Transfer learning with convolutional neural networks for diabetic retinopathy image classification. A review
I Kandel, M Castelli
Applied Sciences 10 (6), 2021, 2020
1602020
Comparative study of first order optimizers for image classification using convolutional neural networks on histopathology images
I Kandel, M Castelli, A Popovič
Journal of imaging 6 (9), 92, 2020
762020
How deeply to fine-tune a convolutional neural network: a case study using a histopathology dataset
I Kandel, M Castelli
Applied Sciences 10 (10), 3359, 2020
672020
Musculoskeletal images classification for detection of fractures using transfer learning
I Kandel, M Castelli, A Popovič
Journal of imaging 6 (11), 127, 2020
262020
Brightness as an augmentation technique for image classification
I Kandel, M Castelli, L Manzoni
Emerging Science Journal 6 (4), 881-892, 2022
252022
Comparing stacking ensemble techniques to improve musculoskeletal fracture image classification
I Kandel, M Castelli, A Popovič
Journal of Imaging 7 (6), 100, 2021
202021
Improving convolutional neural networks performance for image classification using test time augmentation: a case study using MURA dataset
I Kandel, M Castelli
Health information science and systems 9 (1), 33, 2021
192021
The effect of batch size on the generalizability of the convolutional neural networks on a histopathology dataset. ICT Express 6 (4): 312–315
I Kandel, M Castelli
192020
A novel architecture to classify histopathology images using convolutional neural networks
I Kandel, M Castelli
Applied Sciences 10 (8), 2929, 2020
172020
The effect of batch size on the generalizability of the convolutional neural networks on a histopathology dataset, ICT Express, 6, 312–315
I Kandel, M Castelli
82020
Deep Learning Techniques for Medical Image Classification
IHA Kandel
PQDT-Global, 2021
22021
A comparative study of tree-based models for churn prediction: A case study in the telecommunication sector
IHA Kandel
PhD diss, 2019
22019
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