Results 131 to 140 of about 208,635 (216)
Classification of walking speed based on bidirectional LSTM
Walking speed is a powerful predictor of health events which are related to musculoskeletal disorder and mental disease. One of the established computerized technique which employed to perform the gait analysis is motion analysis system.
Low, Wan Shi +4 more
core
Using grilled lamb skewers as a model system, this work builds a multiscale coupling framework from oral processing to retronasal aroma perception, reveals dual‐kinetic release patterns and Electroencephalogram‐characterized central encoding features, and proposes an interpretable physics‐guided deep learning model validated by multiphysics simulation,
Che Shen +12 more
wiley +1 more source
Deep bidirectional LSTM for disease classification supporting hospital admission based on pre-diagnosis: a case study in Vietnam. [PDF]
Nguyen HT +3 more
europepmc +1 more source
Multimodal Stacked Bidirectional LSTM 구조를 활용한 거리 센서 기반의 3D 위치 인식
In this paper, we propose the multimodal stacked bidirectional LSTM that takes range-only measurements as input and outputs robot's position by end-to-end mapping. Out proposed neural networks receive multimodal range measurements.
이준석 +4 more
core
Multimodal Video Summarization Using Vision‐Language Embeddings and Hierarchical Temporal Modeling
Combining BLIP‐2 image captions with CLIP vision–language embeddings gives video frames semantic meaning that pixels alone cannot convey. Processed by a multi‐scale temporal U‐Net and hierarchical shot‐aware transformer, these multimodal features achieve a state‐of‐the‐art 59.27% F1‐score on SumMe using only 28.27M parameters.
Saadman Sakib, Kaushik Deb
wiley +1 more source
ACPred-BMF: bidirectional LSTM with multiple feature representations for explainable anticancer peptide prediction. [PDF]
Han B, Zhao N, Zeng C, Mu Z, Gong X.
europepmc +1 more source
Cross Wavelet Transform (XWT) is combined with a pre‐trained AlexNet to extract rich time‐frequency features from non‐stationary EEG signals. Also, the proposed framework simultaneously extracts and integrates spatial (Node2vec), time‐frequency (XWT + AlexNet), and spectral (PSD + TSCN) features from EEG and ERP signals within a parallel architecture ...
Atefeh Abedzadeh Attar +2 more
wiley +1 more source
Image captioning using bidirectional LSTM neural network
Automatic image captioning is a crucial task in image processing and machine vision, where images are segmented into regions, and captions are assigned based on shared attributes.
Farnaz Hoseini, Anaram Yaghoobi Notash
doaj +1 more source
Prediction model of sparse autoencoder-based bidirectional LSTM for wastewater flow rate. [PDF]
Huang J, Yang S, Li J, Oh J, Kang H.
europepmc +1 more source
The proposed model takes an imbalanced English dataset as input and balances it by Generating Synthetic Tweets (GST) using GPT‐based paraphrasing. These new tweets are then annotated with one of 10 categorical labels representing their primary meaning, using another large language model like GPT.
Hossein Nekouei +1 more
wiley +1 more source

