30 citations · 75 across the 15 of their papers we have counts for
15 papers
Uncertainty Detection and Reduction in Neural Decoding of EEG Signals
Tiehang Duan, Zhenyi Wang, Sheng Liu +2
EEG decoding systems based on deep neural networks have been widely used in decision making of brain computer interfaces (BCI). Their predictions, however, can be unreliable given…
Improving Joint Learning of Chest X-Ray and Radiology Report by Word Region Alignment
Zhanghexuan Ji, Mohammad Abuzar Shaikh, Dana Moukheiber +3
Self-supervised learning provides an opportunity to explore unlabeled chest X-rays and their associated free-text reports accumulated in clinical routine without manual supervision…
LAViTeR: Learning Aligned Visual and Textual Representations Assisted by Image and Caption Generation
Mohammad Abuzar Hashemi, Zhanghexuan Li, Mihir Chauhan +5
Pre-training visual and textual representations from large-scale image-text pairs is becoming a standard approach for many downstream vision-language tasks. The transformer-based m…
Soft-Attention Improves Skin Cancer Classification Performance
Soumyya Kanti Datta, Seyed Mohammad Abuzar Hashemi, Sargur N. Srihari +1
In clinical applications, neural networks must focus on and highlight the most important parts of an input image. Soft-Attention mechanism enables a neural network toachieve this g…
Attention based Writer Independent Handwriting Verification
Mohammad Abuzar Shaikh, Tiehang Duan, Mihir Chauhan +1
The task of writer verification is to provide a likelihood score for whether the queried and known handwritten image samples belong to the same writer or not. Such a task calls for…
Ultra Efficient Transfer Learning with Meta Update for Cross Subject EEG Classification
Tiehang Duan, Mihir Chauhan, Mohammad Abuzar Shaikh +2
The pattern of Electroencephalogram (EEG) signal differs significantly across different subjects, and poses challenge for EEG classifiers in terms of 1) effectively adapting a lear…
Explanation based Handwriting Verification
Mihir Chauhan, Mohammad Abuzar Shaikh, Sargur N. Srihari
Deep learning system have drawback that their output is not accompanied with ex-planation. In a domain such as forensic handwriting verification it is essential to provideexplanati…
Sequential Embedding Induced Text Clustering, a Non-parametric Bayesian Approach
Tiehang Duan, Qi Lou, Sargur N. Srihari +1
Current state-of-the-art nonparametric Bayesian text clustering methods model documents through multinomial distribution on bags of words. Although these methods can effectively ut…
Hybrid Feature Learning for Handwriting Verification
Mohammad Abuzar Shaikh, Seyed Mohammad Abuzar Hashemi, Mihir Chauhan +2
We propose an effective Hybrid Deep Learning (HDL) architecture for the task of determining the probability that a questioned handwritten word has been written by a known writer. H…
Joint Visual Denoising and Classification using Deep Learning
Gang Chen, Yawei Li, Sargur N. Srihari
Visual restoration and recognition are traditionally addressed in pipeline fashion, i.e. denoising followed by classification. Instead, observing correlations between the two tasks…
Word Recognition with Deep Conditional Random Fields
Gang Chen, Yawei Li, Sargur N. Srihari
Recognition of handwritten words continues to be an important problem in document analysis and recognition. Existing approaches extract hand-engineered features from word images--w…
Using Social Dynamics to Make Individual Predictions: Variational Inference with a Stochastic Kinetic Model
Zhen Xu, Wen Dong, Sargur Srihari
Social dynamics is concerned primarily with interactions among individuals and the resulting group behaviors, modeling the temporal evolution of social systems via the interactions…
Generalized K-fan Multimodal Deep Model with Shared Representations
Gang Chen, Sargur N. Srihari
Multimodal learning with deep Boltzmann machines (DBMs) is an generative approach to fuse multimodal inputs, and can learn the shared representation via Contrastive Divergence (CD)…
Sequential Labeling with online Deep Learning
Gang Chen, Ran Xu, Sargur Srihari
Deep learning has attracted great attention recently and yielded the state of the art performance in dimension reduction and classification problems. However, it cannot effectively…
Restricted Boltzmann Machine for Classification with Hierarchical Correlated Prior
Gang Chen, Sargur H. Srihari
Restricted Boltzmann machines (RBM) and its variants have become hot research topics recently, and widely applied to many classification problems, such as character recognition and…