AliAmini93 / ADHDeepNetLinks
ADHDeepNet is a model that integrates temporal and spatial characterization, attention modules, and explainability techniques, optimized for EEG data ADAD diagnosis. Neural Architecture Search (NAS), Hyper-parameter optimization, and data augmentation are also incorporated to enhance the model's performance and accuracy.
☆48Updated last year
Alternatives and similar repositories for ADHDeepNet
Users that are interested in ADHDeepNet are comparing it to the libraries listed below
Sorting:
- Developed the Neuro Vision Transformer, an innovative machine learning model utilizing Vision Transformer architecture for EEG signal cla…☆25Updated 2 years ago
- Autoencoders (AEs) were developed for high-resolution image reconstruction from TinyImageNet and pair recovery from averaged CIFAR-10 com…☆11Updated 2 years ago
- Developed TactileNet, the first deep-learning model designed for surface roughness recognition using EEG data. This project leverages CNN…☆32Updated 3 years ago
- Implemented a CNN-LSTM Action Recognizer for dynamic motion analysis, integrating convolutional and recurrent neural networks to efficien…☆20Updated 2 years ago
- Developed a Windows-based app for analyzing data distributions and identifying the best-fitted distribution using the Maximum Likelihood …☆18Updated 2 years ago
- Developed a Windows tool using PyQt5, integrating K-means clustering for data analysis. The application recommends optimal cluster number…☆26Updated 2 years ago
- In 2021, a precise forecast of Iran Post's 2021-2022 income was achieved using ARIMA, with only a 1.5\% error. This approach was subseque…☆14Updated 2 years ago
- Developed the ViViT model for medical video classification, enhancing 3D organ image analysis using transformer-based architectures.☆27Updated last year
- ☆12Updated last year
- Developed a churn prediction model using XGBoost, with comprehensive data preprocessing and hyperparameter tuning. Applied SHAP for featu…☆22Updated last year
- Developed BERT, LSTM, TFIDF, and Word2Vec models to analyze social media data, extracting service aspects and sentiments from a custom da…☆27Updated last year
- Using DIgSILENT, a smart-grid case study was designed for data collection, followed by feature extraction using FFT and DWT. Post-extract…☆41Updated last year
- Implementing a Graph Neural Network in PyTorch for edge prediction on MNIST images, showcasing a novel approach in connectivity analysis.☆14Updated 2 years ago
- Developed a custom application of the Segment Anything Model (SAM) for breast cancer tissue segmentation, utilizing Hugging Face's Transf…☆38Updated last year
- A 3D Attention U-Net model is developed, aimed at segmenting and tracking Multiple Sclerosis lesions in MRI images.☆41Updated last year
- Projects with Genetic Algorithm (GA), Ant Colony Optimization (ACO), and Particle Swarm Optimization (PSO)☆30Updated last year
- An algorithm for robot navigation was designed, accounting for random obstacles and determining optimal paths. It leverages a genetic alg…☆14Updated 3 years ago
- The optimization of Wireless Sensor Networks (WSNs) using low-power nodes focused on energy efficiency, introducing a routing strategy fo…☆23Updated 3 years ago
- ☆13Updated last year
- Resources to learn how to implement ethical AI☆16Updated last week
- ☆27Updated last year
- This project aims to leverage Amazon Web Services to create trending Youtube videos analytics service. Project contains different data en…☆20Updated 5 months ago
- An Experimental Reimplementation of LLM models for research and development process☆21Updated last year
- ☆875Updated 2 years ago
- ☆40Updated 6 months ago
- ☆411Updated 2 years ago
- Edith Virtual Assistant 🧠☆11Updated 4 years ago
- ☆13Updated 2 years ago
- ☆290Updated last year
- Fine-tuning a quantized Llama 2 chat model on Q&A pairs from counselchat.com to provide empathetic and appropriate mental health advice☆14Updated 2 years ago