Abstract: Semantic segmentation of remote sensing images is challenging due to complex scenes, substantial variations in object scales, and ambiguous boundaries. In this study, we propose a novel ...
For the past few years, a single axiom has ruled the generative AI industry: if you want to build a state-of-the-art model, ...
The implementation is intentionally explicit and educational, avoiding high-level abstractions where possible. . ├── config.py # Central configuration file defining model hyperparameters, training ...
Abstract: Traffic flow prediction is critical for Intelligent Transportation Systems to alleviate congestion and optimize traffic management. The existing basic Encoder-Decoder Transformer model for ...
We break down the Encoder architecture in Transformers, layer by layer! If you've ever wondered how models like BERT and GPT process text, this is your ultimate guide. We look at the entire design of ...
ABSTRACT: To address the challenges of morphological irregularity and boundary ambiguity in colorectal polyp image segmentation, we propose a Dual-Decoder Pyramid Vision Transformer Network (DDPVT-Net ...
Diffusion Transformers have demonstrated outstanding performance in image generation tasks, surpassing traditional models, including GANs and autoregressive architectures. They operate by gradually ...
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