7 citations · 7 across the 6 of their papers we have counts for
7 papers
Modalities Should Talk to Each Other: Dual-Stream Multimodal Learning for Long-Horizon Influenza Forecasting
Seyed Mohammad Hossein Hashemi, Mohsen Hooshmand, Parvin Razzaghi
Forecasting long-range influenza-like illness (ILI) matters for public health readiness. Publicly available surveillance datasets typically pair numeric epidemiological signals wit…
EssentialGIN: a new approach for gene essentiality prediction based on graph isomorphism neural networks
Sahar Mansouri-Rad, Zahra Narimani, Parvin Razzaghi +1
Background: Prediction of essential genes (proteins), is a basic and challenging problem but at the same time very costly and time-consuming in wet-lab experiments. Predicting esse…
PLA-SGCN: Protein-Ligand Binding Affinity Prediction by Integrating Similar Pairs and Semi-supervised Graph Convolutional Network
Karim Abbasi, Parvin Razzaghi, Amin Ghareyazi +1
The protein-ligand binding affinity (PLA) prediction goal is to predict whether or not the ligand could bind to a protein sequence. Recently, in PLA prediction, deep learning has r…
Connective Reconstruction-based Novelty Detection
Seyyed Morteza Hashemi, Parvaneh Aliniya, Parvin Razzaghi
Detection of out-of-distribution samples is one of the critical tasks for real-world applications of computer vision. The advancement of deep learning has enabled us to analyze rea…
Deep Multimodal Image-Text Embeddings for Automatic Cross-Media Retrieval
Hadi Abdi Khojasteh, Ebrahim Ansari, Parvin Razzaghi +1
This paper considers the task of matching images and sentences by learning a visual-textual embedding space for cross-modal retrieval. Finding such a space is a challenging task si…
An Intelligent Safety System for Human-Centered Semi-Autonomous Vehicles
Hadi Abdi Khojasteh, Alireza Abbas Alipour, Ebrahim Ansari +1
Nowadays, automobile manufacturers make efforts to develop ways to make cars fully safe. Monitoring driver's actions by computer vision techniques to detect driving mistakes in rea…
Self-Taught Support Vector Machine
Parvin Razzaghi
In this paper, a new approach for classification of target task using limited labeled target data as well as enormous unlabeled source data is proposed which is called self-taught…