[Review] XAI-Powered Smart Agriculture Framework for Enhancing Food Productivity and Sustainability 1) What the paper sets out to do The article
[Review] A multibranch CNN‑BiLSTM model for human activity recognition using wearable sensor data Source: Challa, S. K., Kumar, A., & Semwal, V. B.
[Review] A Public Domain Dataset for Human Activity Recognition Using Smartphones For Jiahong’s PhD Journal Primary source: Anguita, Ghio, Oneto,
[Review] Recognition method research on rough handling of express parcels based on acceleration features and CNN Paper reviewed: Recognition method research on rough handling of express
End-to-End ML Experiment Tracking with MLflow A practical, reproducible tutorial you can drop into your project
[Review] A Practical Introduction to Sequence Learning Models—RNN, LSTM, GRU (Literature Review) TL;DR: This review distills a concise preprint on sequence
From Local Training to Live API: A Minimal, Reliable CI/CD Workflow Goal: Train your ML model on your local machine, package
[XAI] SHAP vs. LIME in XAI: A Deep, Practical Comparison for Real-World ML TL;DR: LIME is fast, local, and great for quick
[Review] Deep learning models for real-life human activity recognition from smartphone sensor data Paper reviewed: García-González, D., Rivero, D., Fernández-Blanco, E., & Luaces,
[Review] Real-time Human Activity Recognition from Accelerometer Data using Convolutional Neural Networks Article reviewed: Andrey Ignatov (2018), “Real-time human activity recognition from