TMCnet

Bridging Silence: A Real-Time Sign Language to English Text Translation System Using Python, OpenCV, and Convolutional Neural Networks

Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive ...
IEEE

Open-Structure: Structural Benchmark Dataset for SLAM Algorithms

Abstract: This letter presents Open-Structure, a novel benchmark dataset for evaluating visual odometry and SLAM methods. Compared to existing public datasets that primarily offer raw images, ...
The New York Times

The Discount Data That Some Colleges Still Won’t Publish

The Common Data Set can help prospective students know how much aid they could get to pay for college. Why don’t all schools provide it? By Ron Lieber A similar version of this column was published ...
Semiconductor Engineering

Largest High-Quality Verilog Dataset for LLM Fine-Tuning (Univ. of Florida)

A new technical paper titled “VerilogDB: The Largest, Highest-Quality Dataset with a Preprocessing Framework for LLM-based RTL Generation” was published by researchers at the University of Florida.
GitHub

SD3 ControlNet Script (and others?): dataset preprocessing cache depends on unrelated arguments

When using the SD3 ControlNet training script, the training dataset embeddings are precomputed and the results are given a fingerprint based on the input script arguments, which will cause subsequent ...
Scientific Research Publishing

Diabetic Retinopathy Severity Classification Using Data Fusion and Ensemble Transfer Learning ()

Diabetic retinopathy is a serious concern for people dealing with diabetes. Detecting diabetic retinopathy poses significant challenges, requiring skilled professionals, extensive manual image ...
Scientific Research Publishing

Lapp, D. (n.d.) Heart Disease Dataset.

ABSTRACT: Over the past ten years, there has been an increase in cardiovascular disease, one of the most dangerous types of disease. However, cardiovascular detection is a technique that analyzes data ...
IEEE

Exploring the Preprocessing of a Time-Series Healthcare Administrative Dataset on Deep Learning to Improve Prediction

Abstract: Preprocessing methods are important in enhancing prediction performance for time-series administrative data. This study underscores the importance of preprocessing methods by comparing two ...