InfoQ

Netflix Details its In-House LLM Serving Platform with Triton and vLLM

Netflix has described the production lessons behind bringing LLM inference into its internal serving platform, including the ...
IEEE

EEG-Based Four Level Fear Classification using Graph Neural Network and LSTM Fusion Model: Comparing Raw and DE Features with k-Fold and Leave-One-Subject-Out

Abstract: Electroencephalography (EEG)-based four-level fear classification is important for mental-health assessment and emotion-aware systems, yet robust generalization to unseen subjects remains ...
GitHub

microCLIP: Unsupervised CLIP Adaptation via Coarse-Fine Token Fusion for Fine-Grained Image Classification

microCLIP is a lightweight self-training framework that adapts CLIP for fine-grained image classification without requiring labeled data. While CLIP is strong in zero-shot transfer, it primarily ...
Journal of Medical Internet Research

Diabetic Foot Ulcer Classification Models Using Artificial Intelligence and Machine Learning Techniques: Systematic Review

The risk of bias was evaluated using the Quality In Prognosis Studies tool and the Prediction model Risk Of Bias Assessment Tool by 2 investigators (MMS and MAS) independently. A narrative synthesis ...
GitHub

Data for GICS (Global Industry Classification Standard)

This repository provides datasets aligned with the Global Industry Classification Standard (GICS) 2023 edition. The data is ready for integration into database dictionaries, reference systems, and ...
IEEE

Improving the Sound Classification Accuracy Using CNN-LSTM and MFCC with Audio Augmentation for Diagnosing Respiratory Disease

Abstract: Audio is vital information data for understanding various situations. A multitude of sound features can be explained by analysis through the audio signals. Numerous classification methods ...