Papers Multimodal Text and Image Classification
“Multimodal Text and Image Classification” 태그가 달린 논문 7편 · 필터 해제
Harmonic-NAS: Hardware-Aware Multimodal Neural Architecture Search on Resource-constrained Devices
The recent surge of interest surrounding Multimodal Neural Networks (MM-NN) is attributed to their ability to effectively process and integrate multiscale information from diverse data sources. MM-NNs extract and fuse fe…
General ClassificationMultimodal Text and Image ClassificationNeural Architecture SearchCMA-CLIP: Cross-Modality Attention CLIP for Image-Text Classification
Modern Web systems such as social media and e-commerce contain rich contents expressed in images and text. Leveraging information from multi-modalities can improve the performance of machine learning tasks such as classi…
AttributeImage-text ClassificationMultimodal Text and Image Classificationtext-classification+1Detecting Hate Speech in Memes Using Multimodal Deep Learning Approaches: Prize-winning solution to Hateful Memes Challenge
Memes on the Internet are often harmless and sometimes amusing. However, by using certain types of images, text, or combinations of both, the seemingly harmless meme becomes a multimodal type of hate speech -- a hateful …
Ensemble LearningMeme ClassificationMultimodal Deep LearningMultimodal Text and Image ClassificationImage and Text fusion for UPMC Food-101 \\using BERT and CNNs
The modern digital world is becoming more and more multimodal. Looking on the internet, images are often associated with the text, so classification problems with these two modalities are very common. In this paper, we …
ClassificationDocument Text ClassificationGeneral ClassificationImage Classification+3Multimodal price prediction
Price prediction is one of the examples related to forecasting tasks and is a project based on data science. Price prediction analyzes data and predicts the cost of new products. The goal of this research is to achieve a…
Multimodal Text and Image ClassificationPredictionAnalysis of Social Media Data using Multimodal Deep Learning for Disaster Response
Multimedia content in social media platforms provides significant information during disaster events. The types of information shared include reports of injured or deceased people, infrastructure damage, and missing or f…
Deep LearningDisaster ResponseHumanitarianInformativeness+3Are These Birds Similar: Learning Branched Networks for Fine-grained Representations
Fine-grained image classification is a challenging task due to the presence of hierarchical coarse-to-fine-grained distribution in the dataset. Generally, parts are used to discriminate various objects in fine-grained da…
ClassificationDocument Text ClassificationFine-Grained Image ClassificationGeneral Classification+5