UroToday

Semi-supervised learning in prostate MRI tumor detection approaches fully supervised performance on external validation.

To evaluate the diagnostic performance of semi-supervised learning models for aggressive prostate cancer detection on MRI compared to fully supervised models trained with additional expert annotations ...
Carson-Newman University

Active Learning vs. Passive Learning: Why It Matters For Online Students

If you’ve ever finished an online lecture and realized you barely remember what was covered, you’ve experienced the difference between active vs. passive learning. In virtual classrooms, it’s easy to ...
GitHub

Solving Semi-Supervised Few-Shot Learning

We investigate the failures of representative semi-supervised learning methods, e.g., FixMatch and DebiasPL, in the challenging few-shot setup for finetuning a pretrained VLM. Our analyses reveal the ...
IEEE

Unsupervised Feature Selection-Driven Active Learning for Semi-Supervised Automatic ECG Analysis

Abstract: Automatic analysis methods of electrocardiograms (ECGs) usually required large-scale annotated training data, but the annotation process is extremely time-consuming. While semi-supervised ...
The Conversation

Jigsaw puzzles help make mathematics learning more active and fun

Francis Duah does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their ...
GitHub

TRAPO: A Semi-Supervised Reinforcement Learning Framework for Boosting LLM Reasoning.

TraPO is a semi-supervised reinforcement learning framework that bridges unlabeled and labeled samples for training large reasoning models (LRMs). Built upon GRPO, TraPO leverages a small set of ...
IEEE

Specific Emitter Identification Based on Semi-Supervised Active Learning

Abstract: Specific emitter identification (SEI) plays a critical role in the security and management of communication systems, particularly within the context of instrumentation and the Internet of ...
Frontiers

OpenLabCluster: active learning based clustering and classification of animal behaviors based on kinematic body keypoints

Quantifying natural behavior from video recordings is a key component in ethological studies. Markerless pose estimation methods have provided an important step toward that goal by automatically ...
marktechpost

A Coding Guide to Master Self-Supervised Learning with Lightly AI for Efficient Data Curation and Active Learning

In this tutorial, we explore the power of self-supervised learning using the Lightly AI framework. We begin by building a SimCLR model to learn meaningful image representations without labels, then ...
The Conversation

Chalk and talk vs. active learning: what’s holding South African teachers back from using proven methods?

Lizélle Pretorius received funding from UNISA as part of a bursary when completing her PhD. She is currently a member of ISATT (International Study Association of Teachers and Teaching) and the Junior ...