Long Short-Term Memory (LSTM) network with sequence-to-sequence architecture for building conversational chatbots with attention mechanism. lstm-chatbot/ ├── README.md ├── FEATURES.md # Additional ...
This research paper presents a proactive approach to congestion control in IoT networks using an encoder–decoder LSTM (ED-LSTM) model to predict packet loss ratios ahead of time. By forecasting ...
ABSTRACT: This work presents an innovative Intrusion Detection System (IDS) for Edge-IoT environments, based on an unsupervised architecture combining LSTM networks and Autoencoders. Deployed on ...
I've been transcoding videos on handbrake using AV1 which I think is the latest encoder. AV1 on the Mac is often incredibly efficient. I'm talking 3gb -> 300mb efficient. Even tougher material with ...
Beyond tumor-shed markers: AI driven tumor-educated polymorphonuclear granulocytes monitoring for multi-cancer early detection. Clinical outcomes of a prospective multicenter study evaluating a ...
Tech’s biggest players are all in on AV1, but competing codecs and technical limitations might be holding it back. Tech’s biggest players are all in on AV1, but competing codecs and technical ...
Today, virtually every cutting-edge AI product and model uses a transformer architecture. Large language models (LLMs) such as GPT-4o, LLaMA, Gemini and Claude are all transformer-based, and other AI ...
In a nutshell: A recent blog post by software engineer Paul Butler has shed light on a novel technique for concealing data within Unicode characters, specifically emojis. The post explains the concept ...
Abstract: Accurate prediction of blood glucose levels is crucial for automated treatment in diabetic patients. This study proposes a blood glucose prediction model based on an improved attention ...
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