Self-Attention Meets Parallel Memory Networks to Sharpen Text Sentiment Recognition
Researchers have developed a parallel long short-term memory network with self-attention that reaches 91.6 percent accuracy in recognizing sentiment in ...
Researchers have developed a parallel long short-term memory network with self-attention that reaches 91.6 percent accuracy in recognizing sentiment in ...
Researchers have demonstrated a switchable backdoor attack that injects dual tokens through the layers of Vision Transformers, achieving up to ...
A new survey in Machine Learning provides an extensive taxonomy of attention mechanisms and more than thirty Transformer variants that ...
Researchers have developed CNN-SA-RFR, a cosine similarity-based self-attention framework that suppresses redundant filters during CNN training, boosting plant disease classification ...
A new multi-branch deep learning model fusing satellite, weather, soil and extreme climate data predicts winter wheat yields in China ...
A new deep learning system embeds the peak-end rule directly into its architecture, predicting how people will retrospectively judge emotional ...
Researchers have developed AVP-Pro, a two-stage deep learning framework that identifies antiviral peptides and predicts which virus families and specific ...
Researchers have developed BFA-HARF, a tracking framework that aligns visible and thermal features bidirectionally before fusing them with hybrid attention, ...
Researchers in India have developed a hybrid convolutional neural network and vision transformer that fuses text, speech, video and physiological ...
© 2026 Scienmag - Science Magazine
© 2026 Scienmag - Science Magazine