Popular GitHub Repositories for Comparative

Obsei is a low code AI powered automation tool. It can be used in various business flows like social listening, AI based alerting, brand image analysis, comparative study and more .

A Comparative Framework for Multimodal Recommender Systems

?[ChatGPT4NLU] A Comparative Study on ChatGPT and Fine-tuned BERT

Autoencoders for Unsupervised Anomaly Segmentation in Brain MR Images: A Comparative Study

? A Comparative Study on Handwritten Digits Recognition using Classifiers like K-Nearest Neighbours (K-NN), Multiclass Perceptron/Artificial Neural Network (ANN) and Support Vector Machine (SVM) discussing the pros and cons of each algorithm and providing the comparison results in terms of accuracy and efficiecy of each algorithm.

[MedIA 2025] MedIAnomaly: A comparative study of anomaly detection in medical images

[NeurIPS'25] MLLM-CompBench evaluates the comparative reasoning of MLLMs with 40K image pairs and questions across 8 dimensions of relative comparison: visual attribute, existence, state, emotion, temporality, spatiality, quantity, and quality. CompBench covers diverse visual domains, including animals, fashion, sports, and scenes

CompBench evaluates the comparative reasoning of multimodal large language models (MLLMs) with 40K image pairs and questions across 8 dimensions of relative comparison: visual attribute, existence, state, emotion, temporality, spatiality, quantity, and quality. CompBench covers diverse visual domains, including animals, fashion, sports, and scenes.

Officiel implementation of the paper "FlightScope: An Experimental Comparative Review of Aircraft Detection Algorithms in Satellite Imagery"

Github repository for the paper Which Transformer to Favor: A Comparative Analysis of Efficiency in Vision Transformers.

? Research-grade analytics and comparative datasets from Stobix Labs.

Built a sentiment analysis model to predict the sentiment of a Financial News article. A comparative study of different optimizers used for training was done.

This repository contains code from our comparative study on state of the art unsupervised pathology detection and segmentation methods.

Comparative study of ANN, CNN, LSTM, and ARIMA for time-series forecasting

:coconut: Code & Data for Comparative Opinion Summarization via Collaborative Decoding (Iso et al; Findings of ACL 2022)

Implementation of MambaFormer in Pytorch ++ Zeta from the paper: "Can Mamba Learn How to Learn? A Comparative Study on In-Context Learning Tasks"

A comparative study of deep learning models for predicting Channel State Information (CSI) in massive MIMO systems. Integrates COST2100 dataset with STNet compression and evaluates models based on NMSE, RMSE, and spectral efficiency.

Source code and data for the EDM 2022 paper

Comparative Analysis of CNN, RNN and HAN for Text Classification with GloVe Data Model

Code for paper: "Road object detection: a comparative study of deep learning-based algorithms" https://link.springer.com/article/10.1007/s11042-022-12447-5