activity
20192022
most citedFine-Tuning and Training of DenseNet for Histopathology Image Representation Using TCGA Diagnostic Slides

13 citations · 13 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV2022

Learning Binary and Sparse Permutation-Invariant Representations for Fast and Memory Efficient Whole Slide Image Search

Sobhan Hemati, Shivam Kalra, Morteza Babaie +1

Learning suitable Whole slide images (WSIs) representations for efficient retrieval systems is a non-trivial task. The WSI embeddings obtained from current methods are in Euclidean…

cs.CV2021

Beyond Neighbourhood-Preserving Transformations for Quantization-Based Unsupervised Hashing

Sobhan Hemati, H. R. Tizhoosh

An effective unsupervised hashing algorithm leads to compact binary codes preserving the neighborhood structure of data as much as possible. One of the most established schemes for…

eess.IV2021

Pay Attention with Focus: A Novel Learning Scheme for Classification of Whole Slide Images

Shivam Kalra, Mohammed Adnan, Sobhan Hemati +3

Deep learning methods such as convolutional neural networks (CNNs) are difficult to directly utilize to analyze whole slide images (WSIs) due to the large image dimensions. We over…

eess.IV202113 cited

Fine-Tuning and Training of DenseNet for Histopathology Image Representation Using TCGA Diagnostic Slides

Abtin Riasatian, Morteza Babaie, Danial Maleki +19

Feature vectors provided by pre-trained deep artificial neural networks have become a dominant source for image representation in recent literature. Their contribution to the perfo…

cs.CV2020

A non-alternating graph hashing algorithm for large scale image search

Sobhan Hemati, Mohammad Hadi Mehdizavareh, Shojaeddin Chenouri +1

In the era of big data, methods for improving memory and computational efficiency have become crucial for successful deployment of technologies. Hashing is one of the most effectiv…

q-bio.NC2019

Enhancing performance of subject-specific models via subject-independent information for SSVEP-based BCIs

Mohammad Hadi Mehdizavareh, Sobhan Hemati, Hamid Soltanian-Zadeh

Recently, brain-computer interface (BCI) systems developed based on steady-state visual evoked potential (SSVEP) have attracted much attention due to their high information transfe…