Search
Search Results
-
Parstr: partially autoregressive scene text recognition
An autoregressive (AR) decoder for scene text recognition (STR) requires numerous generation steps to decode a text image character by character but...
-
Attentive Multi-Layer Perceptron for Non-autoregressive Generation
Autoregressive (AR) generation almost dominates sequence generation for its efficacy. Recently, non-autoregressive (NAR) generation gains increasing...
-
Prediction of Wind Speed by Using Machine Learning
Due to the depletion of fossil fuel resources and environmental concerns caused by traditional fuel systems in recent years, the share of renewable...
-
Diverse Paraphrasing with Insertion Models for Few-Shot Intent Detection
In contrast to classic autoregressive generation, insertion-based models can predict in a order-free way multiple tokens at a time, which make their...
-
From data to interpretable models: machine learning for soil moisture forecasting
Soil moisture is critical to agricultural business, ecosystem health, and certain hydrologically driven natural disasters. Monitoring data, though,...
-
Nonlinear Neural Network Based Forecasting Model for Predicting COVID-19 Cases
The recent COVID-19 outbreak has severely affected people around the world. There is a need of an efficient decision making tool to improve awareness...
-
PEACook: Post-editing Advancement Cookbook
Automatic post-editing (APE) aims to improve machine translations, thereby reducing human post-editing efforts. Training on APE models has made a...
-
Effects of Multi-sensory Channel Materials and Emotional Situations in Emotion Induction for Affective Driving Studies
During the driving process, the emotional state of the driver affects their performance significantly. To keep the driver in the most suitable state,...
-
A stacked convolutional neural network for detecting the resource tweets during a disaster
Social media platform like Twitter is one of the primary sources for sharing real-time information at the time of events such as disasters, political...
-
A comprehensive study and performance analysis of deep neural network-based approaches in wind time-series forecasting
The increasing energy demand and expansion of power plants are provoking the effects of greenhouse gas emissions and global warming. To mitigate...
-
Randomized Low-Rank Nonlinear RX Detector
Anomaly Detection is an important topic in various application areas, including image analysis and network intrusion detection. The Reed–**aoli (RX)...
-
Research on deformation prediction of tunnel surrounding rock using the model combining firefly algorithm and nonlinear auto-regressive dynamic neural network
Tunnel surrounding rock deformation is dynamic, sensitive to time and space, nonlinear, and highly complicated. By combining the firefly algorithm...
-
A deep learning model enabled multi-event recognition for distributed optical fiber sensing
Fiber optic sensors that utilize backscattered light offer distributed real-time measurements and have been seen tremendous improvements in sensing...
-
A novel cooperative path planning method based on UCR-FCE and behavior regulation for large-scale multi-robot system
Multi-robot cooperative path planning is a significant research area in the domains of intelligent reconnaissance, transportation, and combat. The...
-
Face super-resolution via nonlinear adaptive representation
Face super-resolution is an example of super-resolution technique, where it takes one or multiple observed low-resolution images and then converts...
-
Comparison of adaptive neuro-fuzzy inference system and recurrent neural network in vertical total electron content forecasting
Accurate prediction of total electron content (TEC) is important for monitoring the behavior of the ionosphere and indeed a magnitude of interest to...
-
Utilizing social media for emergency response: a tweet classification system using attention-based BiLSTM and CNN for resource management
During disasters and emergencies, microblogging platforms like Twitter are crucial sources of real-time information. With so much verbal content...
-
Vocoders
In this chapter, we introduce vocoders, which generate waveforms from acoustic features or directly from linguistic features. With the development of...
-
Acoustic Models
In this chapter, we introduce acoustic models, which generate acoustic features from linguistic features or directly from phonemes or characters....
-
Enhanced cross-prompt trait scoring via syntactic feature fusion and contrastive learning
Automated essay scoring aims to evaluate the quality of an essay automatically. It is one of the main educational applications in the field of...
