eLife

Predicting human decision-making across task conditions via individuality transfer

Encoding individual behavioral traits into a low-dimensional latent representation enables the accurate prediction of decision-making patterns across distinct task conditions.
marktechpost

Google Introduces T5Gemma 2: Encoder Decoder Models with Multimodal Inputs via SigLIP and 128K Context

T5Gemma 2 follows the same adaptation idea introduced in T5Gemma, initialize an encoder-decoder model from a decoder-only checkpoint, then adapt with UL2. In the above figure the research team show ...
IEEE

GURNet: A Gated U-Shaped Encoder-Decoder Predictor for Reversible Data Hiding

Abstract: The existing deep learning based reversible data hiding (RDH) predictors typically adopt standard convolutions for extracting features, which inherently fails to capture contextual ...
IEEE

CNN based encoder and decoder model for sign language communication

Abstract: World Health Organization’s report says that there are more than 466 million individuals worldwide who have hearing impairments, with 72 million of them experiencing deafness. In this paper, ...
IEEE

Temporal Convolutional and Fusional Transformer Model With Bi-LSTM Encoder-Decoder for Multi-Time-Window Remaining Useful Life Prediction

Health prediction is crucial for ensuring reliability, minimizing downtime, and optimizing maintenance in industrial systems. Remaining Useful Life (RUL) prediction is a key component of this process; ...
IEEE

EDSOD: An Encoder-Decoder, Diffusion-model, and Swin-Transformer-based Small Object Detector

Abstract: Small object detection (SOD) given aerial images suffers from an information imbalance across different feature scales. This makes it extremely challenging to perform accurate SOD. Existing ...
IEEE

LSTM Encoder-Decoder Model for Short-Term Power Demand Prediction of Vehicles in Urban Driving Environment

Abstract: With the development of vehicular network technology, the prediction of vehicle power demand has become significant in intelligent transportation systems and energy consumption optimization.
IEEE

An Encoder–Decoder Model Based on Spiking Neural Networks for Address Event Representation Object Recognition

Abstract: Address event representation (AER) object recognition task has attracted extensive attention in neuromorphic vision processing. The spike-based and event-driven computation inherent in the ...
IEEE

Multiresolution Encoder-Decoder Convolutional Neural Network for Magnetic Resonance Image Segmentation

Abstract: In image segmentation by deep learning, encoder-decoder Convolutional Neural Network (CNN) architectures are fundamental for creating and learning representations. However, with many filters ...