Playbook Of AI For 2026: Agent, Human And Value

The shift from volume to value requires more than enthusiasm. It requires engineering discipline, business ownership and the ...
Security Info Watch

AI and Machine Learning in Security: Building Smarter, Integrated Systems for a Safer Future

From SOCs to smart cameras, AI-driven systems are transforming security from a reactive to a predictive approach. This ...
IEEE

Adaptive Graph Learning With Semantic Promotability for Domain Adaptation

Abstract: Domain Adaptation (DA) is used to reduce cross-domain differences between the labeled source and unlabeled target domains. As the existing semantic-based DA approaches mainly focus on ...
Frontiers

VAE deep learning model with domain adaptation, transfer learning and harmonization for diagnostic classification from multi-site neuroimaging data

In large public multi-site fMRI datasets, the sample characteristics, data acquisition methods, and MRI scanner models vary across sites and datasets. This non-neural variability obscures neural ...
GitHub

SiamSeg: Self-Training with Contrastive Learning for Unsupervised Domain Adaptation Semantic Segmentation in Remote Sensing

Prediction results of our proposed method. Network Architectural and Cross-domain Image Different. torch=1.10.2,torchvision=0.11.3 and mmcv-full=1.5.0. Recommended use of conda virtual environments ...
IEEE

Federated Domain-Independent Prototype Learning With Alignments of Representation and Parameter Spaces for Feature Shift

Abstract: Federated learning provides a privacy-preserving modeling schema for distributed data, which coordinates multiple clients to collaboratively train a global model. However, data stored in ...
Game Rant

Jujutsu Kaisen: Open Barrier Domains, Explained

Ahmed Rehan Nasir is a contributor from Pakistan. With a Psych degree in hand, Rehan has a knack for picking apart anime and dissecting characters. When he isn't writing features, you'll probably find ...
Frontiers

Mind over matter: consistency monitoring and domain-specific learning

Introduction: Children's naïve understanding of the physical world is permeated with inconsistencies among beliefs. For example, young children who believe that air does not occupy space also believe ...
marktechpost

Stanford Researchers Introduce EntiGraph: A New Machine Learning Method for Generating Synthetic Data to Improve Language Model Performance in Specialized Domains

Artificial intelligence (AI) has made significant strides in recent years, especially with the development of large-scale language models. These models, trained on massive datasets like internet text, ...