Abstract: In this work, we propose a Wavelet-based Deep Auto Encoder-Decoder Network (WDAED) based image compression which takes care of the various frequency components present in an image.
In this paper, we introduce ML-Decoder, a new attention-based classification head. ML-Decoder predicts the existence of class labels via queries, and enables better utilization of spatial data ...
Read full article about: Microsoft follows Anthropic and OpenAI into the AI super app race with overhauled Copilot and AutoPilot agents Microsoft is planning yet another overhauled version of Copilot, ...
Read full article about: Microsoft follows Anthropic and OpenAI into the AI super app race with overhauled Copilot and AutoPilot agents Microsoft is planning yet another overhauled version of Copilot, ...
We note that our work focuses on architectural comparisons rather than competing with recent SLM developments (e.g., SmolLM, MobileLLM). Our analysis isolates the fundamental advantages of ...
Abstract: A new method is given for performing approximate maximum-likelihood (ML) decoding of an arbitrary binary linear code based on observations received from any discrete memoryless symmetric ...
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