37 citations · 50 across the 7 of their papers we have counts for
9 papers
SC-MIL: Supervised Contrastive Multiple Instance Learning for Imbalanced Classification in Pathology
Dinkar Juyal, Siddhant Shingi, Syed Ashar Javed +6
Multiple Instance learning (MIL) models have been extensively used in pathology to predict biomarkers and risk-stratify patients from gigapixel-sized images. Machine learning probl…
Additive MIL: Intrinsically Interpretable Multiple Instance Learning for Pathology
Syed Ashar Javed, Dinkar Juyal, Harshith Padigela +3
Multiple Instance Learning (MIL) has been widely applied in pathology towards solving critical problems such as automating cancer diagnosis and grading, predicting patient prognosi…
Rethinking Machine Learning Model Evaluation in Pathology
Syed Ashar Javed, Dinkar Juyal, Zahil Shanis +3
Machine Learning has been applied to pathology images in research and clinical practice with promising outcomes. However, standard ML models often lack the rigorous evaluation requ…
Towards Low-Cost and Efficient Malaria Detection
Waqas Sultani, Wajahat Nawaz, Syed Javed +3
Malaria, a fatal but curable disease claims hundreds of thousands of lives every year. Early and correct diagnosis is vital to avoid health complexities, however, it depends upon t…
CineFilter: Unsupervised Filtering for Real Time Autonomous Camera Systems
Sudheer Achary, K L Bhanu Moorthy, Syed Ashar Javed +3
Autonomous camera systems are often subjected to an optimization/filtering operation to smoothen and stabilize the rough trajectory estimates. Most common filtering techniques do r…
Embodied Language Grounding with 3D Visual Feature Representations
Mihir Prabhudesai, Hsiao-Yu Fish Tung, Syed Ashar Javed +3
We propose associating language utterances to 3D visual abstractions of the scene they describe. The 3D visual abstractions are encoded as 3-dimensional visual feature maps. We inf…
MergeNet: A Deep Net Architecture for Small Obstacle Discovery
Krishnam Gupta, Syed Ashar Javed, Vineet Gandhi +1
We present here, a novel network architecture called MergeNet for discovering small obstacles for on-road scenes in the context of autonomous driving. The basis of the architecture…
Learning Unsupervised Visual Grounding Through Semantic Self-Supervision
Syed Ashar Javed, Shreyas Saxena, Vineet Gandhi
Localizing natural language phrases in images is a challenging problem that requires joint understanding of both the textual and visual modalities. In the unsupervised setting, lac…
Object-Level Context Modeling For Scene Classification with Context-CNN
Syed Ashar Javed, Anil Kumar Nelakanti
Convolutional Neural Networks (CNNs) have been used extensively for computer vision tasks and produce rich feature representation for objects or parts of an image. But reasoning ab…