Search Results for author:
Found 6 papers, 1 papers with code
CapHDR2IR: Caption-Driven Transfer from Visible Light to Infrared Domain
As an alternative, visible light can be used to synthesize IR images but this causes a loss of fidelity in image details and introduces inconsistencies due to lack of contextual awareness of the scene.
Semantic Aware Diffusion Inverse Tone Mapping
In this paper, we present a novel inverse tone mapping approach for mapping SDR images to HDR that generates lost details in clipped regions through a semantic-aware diffusion based inpainting approach.
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone
We introduce phi-3-mini, a 3. 8 billion parameter language model trained on 3. 3 trillion tokens, whose overall performance, as measured by both academic benchmarks and internal testing, rivals that of models such as Mixtral 8x7B and GPT-3. 5 (e. g., phi-3-mini achieves 69% on MMLU and 8. 38 on MT-bench), despite being small enough to be deployed on a phone.
Ranked #5 on
MMR total
on MRR-Benchmark
(using extra training data)
G-SemTMO: Tone Mapping with a Trainable Semantic Graph
In this work, we draw inspiration from an expert photographer's approach and present a Graph-based Semantic-aware Tone Mapping Operator, G-SemTMO.
Example-Based Named Entity Recognition
We present a novel approach to named entity recognition (NER) in the presence of scarce data that we call example-based NER.
Machine Learning at Microsoft with ML .NET
Machine Learning is transitioning from an art and science into a technology available to every developer.
