SoyabulIslamLincoln

awesome-notebooks

+100 awesome Jupyter Notebooks templates, organized by tools, published by the Naas community, to kickstart your data projects in minutes. 😎

complete-javascript-course

Starter files, final projects and FAQ for my Complete JavaScript course

Deep-Learning-Based-Radio-Signal-Classification

Final Project for AI Wireless

deep-learning-models

Keras code and weights files for popular deep learning models.

EmotionsInTheWild-CNN-Benchmarks

Emotion (Context + Facial) recognition in the wild using ConvNets (EfficientNet, ResNet, ResNext)

geospatial-data-catalogs

A list of open geospatial datasets available on AWS, Earth Engine, Planetary Computer, NASA CMR, and STAC Index

Optimizing-Modulation-Classification-with-Deep-Learning

Radio-Modulation-Recognition-Networks

Radio modulation recognition with CNN, CLDNN, CGDNN and MCTransformer architectures. Best results were achieved with the CGDNN architecture, which has roughly 50,000 parameters, and the final model has a memory footprint of 636kB. More details can be found in my bachelor thesis linked in the readme file.

ResNet-for-Radio-Recognition

Implementation and improvement of "Over the Air Deep Learning Based Radio Signal Classification"

Tools-to-Design-or-Visualize-Architecture-of-Neural-Network

Tools to Design or Visualize Architecture of Neural Network

SoyabulIslamLincoln/awesome-notebooks

+100 awesome Jupyter Notebooks templates, organized by tools, published by the Naas community, to kickstart your data projects in minutes. 😎

SoyabulIslamLincoln/Deep-Learning-Based-Radio-Signal-Classification

Final Project for AI Wireless

SoyabulIslamLincoln/EmotionsInTheWild-CNN-Benchmarks

Emotion (Context + Facial) recognition in the wild using ConvNets (EfficientNet, ResNet, ResNext)

SoyabulIslamLincoln/geospatial-data-catalogs

A list of open geospatial datasets available on AWS, Earth Engine, Planetary Computer, NASA CMR, and STAC Index

SoyabulIslamLincoln/5G-NR-data-generato

The source code of the paper "5G MIMO-CSI: a data generator configuring to 5G NR channel standard and its application" is provided in the warehouse, and the data generator can be downloaded for free by researchers

SoyabulIslamLincoln/annotated_deep_learning_paper_implementations

🧑‍🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

SoyabulIslamLincoln/Applied-Deep-Learning

Applied Deep Learning Course

SoyabulIslamLincoln/codealpha_task

SoyabulIslamLincoln/COSCO

[TPDS'21] COSCO: Container Orchestration using Co-Simulation and Gradient Based Optimization for Fog Computing Environments

SoyabulIslamLincoln/CPPCode

SoyabulIslamLincoln/CSE_3210_1909010

SoyabulIslamLincoln/Deep-Reinforcement-Learning-Hands-On

Hands-on Deep Reinforcement Learning, published by Packt

SoyabulIslamLincoln/DeepRoadNet

SoyabulIslamLincoln/detoxify

Trained models & code to predict toxic comments on all 3 Jigsaw Toxic Comment Challenges. Built using ⚡ Pytorch Lightning and 🤗 Transformers. For access to our API, please email us at contact@unitary.ai.

SoyabulIslamLincoln/ECE_3200_lane_following_robot

SoyabulIslamLincoln/EEG_real_time_seizure_detection

Real-Time Seizure Detection using EEG: A Comprehensive Comparison of Recent Approaches under a Realistic Setting (CHIL 2022)

SoyabulIslamLincoln/gradsflow

An open-source AutoML Library in PyTorch

SoyabulIslamLincoln/heartrate_analysis_python

Python Heart Rate Analysis Package, for both PPG and ECG signals

SoyabulIslamLincoln/imgaug

Image augmentation for machine learning experiments.

SoyabulIslamLincoln/ivy

The Unified Machine Learning Framework

SoyabulIslamLincoln/Java

SoyabulIslamLincoln/MoDANet

In the paper, a multi-task deep convolutional neural network, namely MoDANet, is proposed to perform modulation classification and DOA estimation simultaneously. In particular, the network architecture is designed with multiple residual modules, which tackle the vanishing gradient problem. The multi-task learning (MTL) efficiency of MoDANet was evaluated with different variants of Y-shaped connection and fine-tuning some hyper-parameters of the deep network. As a result, MoDANet with one shared residual module using more filters, larger filter size, and longer signal length can achieve better performance of modulation classification and DOA estimation, but those might result in higher computational complexity. Therefore, choosing these parameters to attain a good trade-off between accuracy and computational cost is important, especially for resource-constrained devices. The network is investigated with two typical propagation channel models, including Pedestrian A and Vehicular A, to show the affect of those channels on the efficiency of the network. Remarkably, our work is the first DL-based MTL model to handle two unrelated tasks of modulation classification and DOA estimation. Please cite the papar as:

SoyabulIslamLincoln/OpenCV_new

SoyabulIslamLincoln/PostgreSQL

SoyabulIslamLincoln/SA-UNet

The open source code of SA-UNet: Spatial Attention U-Net for Retinal Vessel Segmentation.

SoyabulIslamLincoln/Soyabul_islam_KUET_task

SoyabulIslamLincoln/SoyabulIslamLincoln

SoyabulIslamLincoln/start-machine-learning

A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in 2022 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art techniques!

SoyabulIslamLincoln/vision

Datasets, Transforms and Models specific to Computer Vision

SoyabulIslamLincoln/yolov5

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite