[CADL'22, ECCVW] Official repository of paper titled "EdgeNeXt: Efficiently Amalgamated CNN-Transformer Architecture for Mobile Vision Applications".

😎 A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, Agent, and Beyond

MedViT: A Robust Vision Transformer for Generalized Medical Image Classification (Computers in Biology and Medicine 2023)

Hybrid model of Gradient Boosting Trees and Logistic Regression (GBDT+LR) on Spark

Analyzing the Drugs Descriptions, conditions, reviews and then recommending it using Deep Learning Models, for each Health Condition of a Patient.

📖 mmCIF support for hybrid/integrative models

Detecting depressed Patient based on Speech Activity, Pauses in Speech and Using Deep learning Approach

[MICCAI 2024] HySparK: Hybrid Sparse Masking for Large Scale Medical Image Pre-Training

We use our VDEmodel. Our purpose is that predict the distance between car based on Deep-Learning.

This repository is the official implementation of the Hybrid Self-Attention NEAT algorithm. It contains the code to reproduce the results presented in the original paper: https://link.springer.com/article/10.1007/s12530-023-09510-3

Django React Boilerplate Template - Hybrid Model, with Session authentication and CSRF Protection

The main aim of the project is to develop a sentiment analyzer that can be used on twitter data to classify it as positive or negative. Our project takes care of the challenge of bilingual comments, where people tweet in two languages, in this case Hindi and English, in the Latin Alphabet.

Implementation of a new hybrid machine learning technique for multi-fidelity surrogates of finite elements models with applications in multi-physics modeling of soft tissues.

https://teacher.bupt.edu.cn/zhuchuang/en/index.htm

This repository began as a 7th-semester minor project and evolved into our 8th-semester major project, "Advanced Stock Price Forecasting Using a Hybrid Model of Numerical and Textual Analysis." It utilizes Python, NLP (NLTK, spaCy), ML models, Grafana, InfluxDB, and Streamlit for data analysis and visualization.

This research proposed an Advanced DDoS Attack Detection System (ADADS) using a Hybrid Detection Model (HDM) and Continuous Learning Model (CLM) for dynamic adaptation to evolving attack patterns.

A Hybrid Neural Network Approach for Increasing the Absolute Accuracy of Industrial Robots

An integrated autoencoder-based hybrid CNN-LSTM model for COVID-19 severity prediction from lung ultrasound

A Hybrid Model for Role-related User Classification on Twitter

Building the best machine learning model to detect phishing websites.