IEEE

Out-of-Distribution Semantic Segmentation with Disentangled and Calibrated Representation

Abstract: Out-of-distribution (OoD) semantic segmentation aims to recognize pixels of classes undefined in the training dataset. Existing methods mostly focus on training the model to fit real OoD ...
IEEE

Optimized Ensemble Learning for Semantic Segmentation of Satellite Imagery Using DeepLabV3+ and UNet With PSO and Cross-Dataset Evaluation

Abstract: Semantic segmentation is critical in remote sensing applications such as urban planning, disaster management, and environmental monitoring. However, segmenting complex satellite images ...
Reuters

OpenAI says China's DeepSeek trained its AI by distilling US models, memo shows

Feb 12 (Reuters) - OpenAI has warned U.S. lawmakers that Chinese artificial intelligence startup DeepSeek is targeting the ChatGPT maker and the nation's leading AI companies to replicate models and ...
GitHub

Symdex-100

Semantic fingerprints for intent-based Python code search — 50–100x faster index lookups, 10–50x fewer tokens for AI agents. Symdex-100 generates compact, structured metadata ("Cyphers") for every ...
GitHub

Vision model for object detection and segmentation using TENNs State Space Model neural network.

State Space Models (SSMs) are emerging as a practical alternative to transformers, offering similar or better performance with significantly fewer parameters and lower compute requirements. Mamba, the ...