Abstract: The computational complexity of the Transformer model grows quadratically with input sequence length. This causes a sharp increase in computational cost and memory consumption for ...
The degradation is subtle but cumulative. Tools that release frequent updates while training on datasets polluted with ...
The final, formatted version of the article will be published soon. Abstract. Denial-of-service (DoS) attacks pose a major threat to various kinds of computer networks. There are several kinds of ...
Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
Artificial-intelligence agents have their own social-media platform and are publishing AI-generated research papers on their own preprint server.
Researchers at the Department of Energy's Oak Ridge National Laboratory have developed a deep learning algorithm that ...
Abstract: Plant disease identification through leaves is an important aspect of crop health management for achieving the highest productivity. This research work compares the use of pre-trained ...
Abstract: Avocado cultivation is a rapidly growing industry known for its creamy, nutritious fruit and economic value In Tamil Nadu the plane bear fruits for a period of 3 to 4 years after which tree ...
Implementation of Federated Learning Algorithms for Non Independent and Identically Distributed Data
Abstract: Federated Learning (FL) has emerged as a transformative approach for training machine learning models across decentralized data sources while preserving privacy. This study evaluates the ...
Résumé screeners, keyword-matching tools, AI-assisted video interviews are filtering applicants. For job seekers, the challenge is about learning how to pass digital gatekeepers ...
Abstract: Food spoilage detection is critical in ensuring food safety and reducing waste. In this work, we offer a new neural network model, rotOrNot, intended for image analysis-based rotten food ...
In this paper, a novel approach is proposed for early recognition of Radar Work Mode, which integrates a hybrid CNN-Transformer architecture and a Reinforcement Learning strategy. The model processes ...
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