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Found 11 papers, 4 papers with code
A Dataset of Open-Domain Question Answering with Multiple-Span Answers
Multi-span answer extraction, also known as the task of multi-span question answering (MSQA), is critical for real-world applications, as it requires extracting multiple pieces of information from a text to answer complex questions.
OmniAL: A Unified CNN Framework for Unsupervised Anomaly Localization
Besides that, we make the first attempt to conduct a comprehensive study on the robustness of unsupervised anomaly localization and detection methods against different level adversarial attacks.
Using deep convolutional neural networks to classify poisonous and edible mushrooms found in China
It is counted that there are thousands of kinds of mushrooms among which only around 900 types are edible, thus without specialized knowledge, the probability of eating toxic mushrooms by mistake is very high.
ASTF: Visual Abstractions of Time-Varying Patterns in Radio Signals
A time-frequency diagram is a commonly used visualization for observing the time-frequency distribution of radio signals and analyzing their time-varying patterns of communication states in radio monitoring and management.
Transgender Community Sentiment Analysis from Social Media Data: A Natural Language Processing Approach
Transgender community is experiencing a huge disparity in mental health conditions compared with the general population.
Network Anomaly Detection Using Federated Learning and Transfer Learning
In the second learning stage, Ot uses the transfer learning method to reconstruct and re-train the model to further improve the detection performance on the specific task.
An early prediction of covid-19 associated hospitalization surge using deep learning approach
The global pandemic caused by COVID-19 affects our lives in all aspects.
Reverse-engineering Bar Charts Using Neural Networks
Reverse-engineering bar charts extracts textual and numeric information from the visual representations of bar charts to support application scenarios that require the underlying information.
Simultaneous Semantic Alignment Network for Heterogeneous Domain Adaptation
In this paper, we propose a Simultaneous Semantic Alignment Network (SSAN) to simultaneously exploit correlations among categories and align the centroids for each category across domains.
Pythia: AI-assisted Code Completion System
In this paper, we propose a novel end-to-end approach for AI-assisted code completion called Pythia.
Using Deep Learning and Machine Learning to Detect Epileptic Seizure with Electroencephalography (EEG) Data
The prediction of epileptic seizure has always been extremely challenging in medical domain.
