activity
20182022
most citedMitigating the Hubness Problem for Zero-Shot Learning of 3D Objects

21 citations · 34 across the 9 of their papers we have counts for

collaborators

20 papers

cs.CV20222 cited

Exemplar Guided Deep Neural Network for Spatial Transcriptomics Analysis of Gene Expression Prediction

Yan Yang, Md Zakir Hossain, Eric A Stone +1

Spatial transcriptomics (ST) is essential for understanding diseases and developing novel treatments. It measures gene expression of each fine-grained area (i.e., different windows…

cs.CV20223 cited

Less is More: Facial Landmarks can Recognize a Spontaneous Smile

Md. Tahrim Faroque, Yan Yang, Md Zakir Hossain +3

Smile veracity classification is a task of interpreting social interactions. Broadly, it distinguishes between spontaneous and posed smiles. Previous approaches used hand-engineere…

cs.CV2022

Prompt-guided Scene Generation for 3D Zero-Shot Learning

Majid Nasiri, Ali Cheraghian, Townim Faisal Chowdhury +3

Zero-shot learning on 3D point cloud data is a related underexplored problem compared to its 2D image counterpart. 3D data brings new challenges for ZSL due to the unavailability o…

cs.AI2022

Rethinking Task-Incremental Learning Baselines

Md Sazzad Hossain, Pritom Saha, Townim Faisal Chowdhury +3

It is common to have continuous streams of new data that need to be introduced in the system in real-world applications. The model needs to learn newly added capabilities (future t…

q-bio.QM20228 cited

DPST: De Novo Peptide Sequencing with Amino-Acid-Aware Transformers

Yan Yang, Zakir Hossain, Khandaker Asif +3

De novo peptide sequencing aims to recover amino acid sequences of a peptide from tandem mass spectrometry (MS) data. Existing approaches for de novo analysis enumerate MS evidence…

cs.CV2021

Learning without Forgetting for 3D Point Cloud Objects

Townim Chowdhury, Mahira Jalisha, Ali Cheraghian +1

When we fine-tune a well-trained deep learning model for a new set of classes, the network learns new concepts but gradually forgets the knowledge of old training. In some real-lif…