2 citations · 5 across the 13 of their papers we have counts for
16 papers
EarthAlign: Learning Language-Aligned Representations of Earth System Data
Fadillah Adamsyah Maani, Numan Saeed, Jiaqi Ma +4
Interpreting Earth system conditions is central to understanding environmental risks and informing decisions across weather- and climate-sensitive sectors. Existing multimodal weat…
TerraBench: Can Agents Reason Over Heterogeneous Earth-System Data?
Dat Tien Nguyen, Thao Nguyen, Fadillah Adamsyah Maani +5
Climate and environmental decision-making increasingly requires reasoning across heterogeneous inputs, including gridded physical data, satellite imagery, geospatial context, and s…
DARK: Diagonal-Anchored Repulsive Knowledge Distillation for Vision-Language Models under Extreme Compression
Numan Saeed, Asif Hanif, Fadillah Adamsyah Maani +2
Compressing vision-language models for on-device deployment is increasingly important in clinical settings, but knowledge distillation (KD) degrades sharply when the teacher-studen…
DuPLUS: Dual-Prompt Vision-Language Framework for Universal Medical Image Segmentation and Prognosis
Numan Saeed, Tausifa Jan Saleem, Fadillah Maani +3
Deep learning for medical imaging is hampered by task-specific models that lack generalizability and prognostic capabilities, while existing 'universal' approaches suffer from simp…
FetalCLIP: A Visual-Language Foundation Model for Fetal Ultrasound Image Analysis
Fadillah Maani, Numan Saeed, Tausifa Saleem +8
Foundation models are becoming increasingly effective in the medical domain, offering pre-trained models on large datasets that can be readily adapted for downstream tasks. Despite…
Optimizing Brain Tumor Segmentation with MedNeXt: BraTS 2024 SSA and Pediatrics
Sarim Hashmi, Juan Lugo, Abdelrahman Elsayed +6
Identifying key pathological features in brain MRIs is crucial for the long-term survival of glioma patients. However, manual segmentation is time-consuming, requiring expert inter…
All Languages Matter: Evaluating LMMs on Culturally Diverse 100 Languages
Ashmal Vayani, Dinura Dissanayake, Hasindri Watawana +66
Existing Large Multimodal Models (LMMs) generally focus on only a few regions and languages. As LMMs continue to improve, it is increasingly important to ensure they understand cul…
SurvCORN: Survival Analysis with Conditional Ordinal Ranking Neural Network
Muhammad Ridzuan, Numan Saeed, Fadillah Adamsyah Maani +2
Survival analysis plays a crucial role in estimating the likelihood of future events for patients by modeling time-to-event data, particularly in healthcare settings where predicti…
On Enhancing Brain Tumor Segmentation Across Diverse Populations with Convolutional Neural Networks
Fadillah Maani, Anees Ur Rehman Hashmi, Numan Saeed +1
Brain tumor segmentation is a fundamental step in assessing a patient's cancer progression. However, manual segmentation demands significant expert time to identify tumors in 3D mu…
TiBiX: Leveraging Temporal Information for Bidirectional X-ray and Report Generation
Santosh Sanjeev, Fadillah Adamsyah Maani, Arsen Abzhanov +4
With the emergence of vision language models in the medical imaging domain, numerous studies have focused on two dominant research activities: (1) report generation from Chest X-ra…
SurvRNC: Learning Ordered Representations for Survival Prediction using Rank-N-Contrast
Numan Saeed, Muhammad Ridzuan, Fadillah Adamsyah Maani +3
Predicting the likelihood of survival is of paramount importance for individuals diagnosed with cancer as it provides invaluable information regarding prognosis at an early stage.…
Advanced Tumor Segmentation in Medical Imaging: An Ensemble Approach for BraTS 2023 Adult Glioma and Pediatric Tumor Tasks
Fadillah Maani, Anees Ur Rehman Hashmi, Mariam Aljuboory +3
Automated segmentation proves to be a valuable tool in precisely detecting tumors within medical images. The accurate identification and segmentation of tumor types hold paramount…
CoReEcho: Continuous Representation Learning for 2D+time Echocardiography Analysis
Fadillah Adamsyah Maani, Numan Saeed, Aleksandr Matsun +1
Deep learning (DL) models have been advancing automatic medical image analysis on various modalities, including echocardiography, by offering a comprehensive end-to-end training pi…
ConDiSR: Contrastive Disentanglement and Style Regularization for Single Domain Generalization
Aleksandr Matsun, Numan Saeed, Fadillah Adamsyah Maani +1
Medical data often exhibits distribution shifts, which cause test-time performance degradation for deep learning models trained using standard supervised learning pipelines. This c…
SimLVSeg: Simplifying Left Ventricular Segmentation in 2D+Time Echocardiograms with Self- and Weakly-Supervised Learning
Fadillah Maani, Asim Ukaye, Nada Saadi +2
Echocardiography has become an indispensable clinical imaging modality for general heart health assessment. From calculating biomarkers such as ejection fraction to the probability…
Exploring the Transfer Learning Capabilities of CLIP in Domain Generalization for Diabetic Retinopathy
Sanoojan Baliah, Fadillah A. Maani, Santosh Sanjeev +1
Diabetic Retinopathy (DR), a leading cause of vision impairment, requires early detection and treatment. Developing robust AI models for DR classification holds substantial potenti…