mtliba

360-images-VGG-based-Autoencoder-Pytorch

PyTorch implementation of Autoencoder for 360 images , the encoder leverage vgg convolutions weight

360-latent-attention-stream

ATSal

360 video Head and Eye movement prediction framework with two-stream models

Classification-REST-API

Keras imagenet classification REST API , VGG , ResNet50 , InceptionV3 , Xception

Creating-a-Containerized-Web-Application-with-docker-compose

Tutorial : Guide to Creating a Containerized Web Application With docker-compose

Deploying-Containerized-Machine-Learning-model-REST-API-

Deploying ML model in production ,Nginx web server , Gunicorn, Flask ,dockercompose

extend_2d_saliency_model_for_360_video

pytorch-implement-vgg-on-custom-dataset

this project is a trainable implementation of all vgg network versions on a costum dataset .

SalEMA-multi-expert-on-CMP

Create two versions of an existed model for dynamic saliency prediction on 2D video, new models are designed to predict saliency on 360 videos

VAE-deconv-keras

keras implementation of Variational Autoencoder

mtliba/ATSal

360 video Head and Eye movement prediction framework with two-stream models

mtliba/360-images-VGG-based-Autoencoder-Pytorch

PyTorch implementation of Autoencoder for 360 images , the encoder leverage vgg convolutions weight

mtliba/360-latent-attention-stream

mtliba/Deploying-Containerized-Machine-Learning-model-REST-API-

Deploying ML model in production ,Nginx web server , Gunicorn, Flask ,dockercompose

mtliba/pytorch-implement-vgg-on-custom-dataset

this project is a trainable implementation of all vgg network versions on a costum dataset .

mtliba/Creating-a-Containerized-Web-Application-with-docker-compose

Tutorial : Guide to Creating a Containerized Web Application With docker-compose

mtliba/extend_2d_saliency_model_for_360_video

mtliba/SalEMA-multi-expert-on-CMP

Create two versions of an existed model for dynamic saliency prediction on 2D video, new models are designed to predict saliency on 360 videos

mtliba/VAE-deconv-keras

keras implementation of Variational Autoencoder

mtliba/Classification-REST-API

Keras imagenet classification REST API , VGG , ResNet50 , InceptionV3 , Xception

mtliba/beginner-guide-to-PyTorch

mtliba/two_stream_model-tensorflow

extend 2D static saliency model in two stream encoder , the model intend to shift doctor attention in medical images

mtliba/Variational-autoencoder-PyTorch

Variational autoencoder implementation Pytorch

mtliba/Reproduced-VR-EyeTracking

mtliba/segmentation_models

Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

mtliba/A_Guide_to_Running_Tensorflow_Models_on_Android

This is the code for"A Guide to Running Tensorflow Models on Android" By SIraj Raval on Youtube

mtliba/deepmedic

Efficient Multi-Scale 3D Convolutional Neural Network for Segmentation of 3D Medical Scans

mtliba/saliency

Contextual Encoder-Decoder Network for Visual Saliency Prediction [Neural Networks 2020]

mtliba/deep_learning_coronavirus_cure

Using deep learning to generate novel molecules as candidates for binding with coronavirus protease

mtliba/examples

Kubernetes application example tutorials

mtliba/Machine-Learning-with-Python

Machine Learning Implementations in Python

mtliba/medical-imaging-datasets

A list of Medical imaging datasets.

mtliba/salgan

SalGAN: Visual Saliency Prediction with Generative Adversarial Networks

mtliba/stylegan

StyleGAN - Official TensorFlow Implementation

mtliba/TASED-Net

Temporally-Aggregating Spatial Encoder-Decoder Network for Video Saliency Detection (ICCV 2019)

mtliba/KOA_NLCS2024

mtliba/MAE-EyeTracking-Evaluation

mtliba/PQCA-ICASSP2024

mtliba/qomex24