20 citations · 43 across the 9 of their papers we have counts for
9 papers
Pathologist Attention-Aligned Report Generation for Prostate Histopathology
Ruoyu Xue, Suryakant Singh, Souradeep Chakraborty +12
The allocation of visual attention by pathologists during cancer diagnosis is a highly selective process that critically shapes the information extracted from whole-slide images (W…
Measuring and Predicting Where and When Pathologists Focus their Visual Attention while Grading Whole Slide Images of Cancer
Souradeep Chakraborty, Ruoyu Xue, Rajarsi Gupta +11
The ability to predict the attention of expert pathologists could lead to decision support systems for better pathology training. We developed methods to predict the spatio-tempora…
Predicting Visual Attention in Graphic Design Documents
Souradeep Chakraborty, Zijun Wei, Conor Kelton +4
We present a model for predicting visual attention during the free viewing of graphic design documents. While existing works on this topic have aimed at predicting static saliency…
Decoding the visual attention of pathologists to reveal their level of expertise
Souradeep Chakraborty, Dana Perez, Paul Friedman +7
We present a method for classifying the expertise of a pathologist based on how they allocated their attention during a cancer reading. We engage this decoding task by developing a…
Self-supervised co-salient object detection via feature correspondence at multiple scales
Souradeep Chakraborty, Dimitris Samaras
Our paper introduces a novel two-stage self-supervised approach for detecting co-occurring salient objects (CoSOD) in image groups without requiring segmentation annotations. Unlik…
Unsupervised and semi-supervised co-salient object detection via segmentation frequency statistics
Souradeep Chakraborty, Shujon Naha, Muhammet Bastan +2
In this paper, we address the detection of co-occurring salient objects (CoSOD) in an image group using frequency statistics in an unsupervised manner, which further enable us to d…
Visual attention analysis of pathologists examining whole slide images of Prostate cancer
Souradeep Chakraborty, Ke Ma, Rajarsi Gupta +4
We study the attention of pathologists as they examine whole-slide images (WSIs) of prostate cancer tissue using a digital microscope. To the best of our knowledge, our study is th…
Capturing Financial markets to apply Deep Reinforcement Learning
Souradeep Chakraborty
In this paper we explore the usage of deep reinforcement learning algorithms to automatically generate consistently profitable, robust, uncorrelated trading signals in any general…
A dense subgraph based algorithm for compact salient image region detection
Souradeep Chakraborty, Pabitra Mitra
We present an algorithm for graph based saliency computation that utilizes the underlying dense subgraphs in finding visually salient regions in an image. To compute the salient re…