[ECCV 2022] IS-MVSNet: Importance-sampling-based MVSNet
The official code for "TaxDiff: Taxonomic-Guided Diffusion Model for Protein Sequence Generation"
一个比较全面的文本挖掘过程。包含了利用机器学习和文本挖掘技术完成情感分析模型搭建；利用情感极性判断与程度计算来判断情感倾向；利用词频和TF-IDF挖掘出正负文本中的关键点情况；利用文本挖掘相关算法找到平台中用户讨论的集中点。
A privacy-preserving computing system based on TEE.
Density Based Clustering of Applications with Noise (DBSCAN) and Related Algorithms in C++
A Rust-based, OpenAI-style API server for large language models (LLMs)
Phishers Develop the websites similar to those real websites. So, this project comes to know whether the URL is phishing or not.
lda2vec pytorch implementation
AI Voice Agents: Exploring the Next Generation of Human-Machine Interaction! 🎙️🤖🎧
Solutions for NLP-related competition
MoodZik is a web app that utilizes Machine Learning to analyze its user's face through their webcam, identify their current emotions, and compose music based on how they are feeling.
This project is a dynamic pricing system based on machine learning and game theory. It analyzes complex customer behaviors and historical transaction data to generate intelligent, differentiated pricing strategies, aiming to maximize expected revenue. 本项目是一个基于机器学习与博弈论的动态定价系统。系统通过深度分析复杂的客户行为与历史交易数据，生成智能、差异化的定价策略，旨在实现预期收益的最大化。
A time slicer for training and testing temporally correlated Machine Learning models.
IMU2Text: A hybrid CNN+GNN pipeline for handwriting recognition and trajectory prediction using IMU data with state-of-the-art accuracy (99.74%).
Classification of hematogones & neoplastic B lymphoblasts through computational analysis of immunophenotypic flow cytometry data to improve B cell acute lymphoblastic leukemia treatment
In the real estate industry, the determination of rental prices plays a critical role in shaping the interactions between property owners, tenants, and property management companies. The ever-changing nature of the real estate market necessitates a dynamic and data-driven approach to set competitive and fair rental prices.
The Food Price Estimation project focuses on providing estimates of food prices to capture local price fluctuations in regions where people are vulnerable to localized price surges. The project utilizes a machine-learning algorithm designed to predict ongoing subnational price surveys, demonstrating accuracy comparable to direct price measurements.
Anomaly detection algorithm related papers, competition schemes, codes, etc
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