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Name: Mohammadhossein Modir Rousta
Type: User
Blog: https://www.linkedin.com/in/mohammad-hossein-modirrousta/
Mohammadhossein Modir Rousta's Projects
20_iccsa_rg_gan
New approach based on Generative Adversarial Network (GAN) and Support Vector Machine (SVM) to identify in-silico candidates for reference genes.
bone-fracture-classification
This project uses PyTorch to classify bone fractures. As well as fine-tuning some famous CNN architectures (like VGG 19, MobileNetV3, RegNet,...), we designed our own architecture. Additionally, we used Transformer architectures (such as Vision Transformer and Swin Transformer). This dataset is Bone Fracture Multi-Region X-ray, available on Kaggle.
chest-x-ray-image_segmentation_resunet
Lung segmentation for chest X-Ray images with ResUNet and UNet. In addition, feature extraction and tuberculosis cases diagnosis had developed.
control-of-unstable-processes-with-time-delays-via-adrc
Control of unstable processes with time delays via ADRC.
deep-neural-networks-with-pytorch
This is a implementation for Deep Neural Networks with PyTorch (Coursera)
face-mask-detection_detr
This is a face mask detection project implemented with the Pytorch. We use End-to-End Object Detection with Transformers model (DETR) and Face Mask Detection dataset available on kaggle.
har-wisdm-cnn
Human Activity Recognition on the Wireless Sensor Data Mining (WISDM) dataset using Convolutional Neural Network and Convolutional Autoencoder
induction-motor-faults-detection-with-stacking-ensemble-method-and-deep-learning
This is a induction motor faults detection project implemented with Tensorflow. We use Stacking Ensembles method (with Random Forest, Support Vector Machine, Deep Neural Network and Logistic Regression) and Machinery Fault Dataset dataset available on kaggle.
introduction-to-deep-learning-and-neural-networks-with-keras
This is a implementation for Introduction to Deep Learning and Neural Networks with Keras (Coursera)
neural-networks-and-deep-learning
This is a implementation for Neural Networks and Deep Learning (Coursera) by Andrew Ng
surface-crack-detection-with-dl
This is a Surface Crack Detection project implemented with the Tensorflow. We fine tuning some deep learning models (like VGG 19, VGG16, MobileNetV2, ...). Use Surface Crack Detection dataset available on kaggle.
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