35 citations · 56 across the 8 of their papers we have counts for
9 papers
DGRNet: Disagreement-Guided Refinement for Uncertainty-Aware Brain Tumor Segmentation
Bahram Mohammadi, Yanqiu Wu, Vu Minh Hieu Phan +6
Accurate brain tumor segmentation from MRI scans is critical for diagnosis and treatment planning. Despite the strong performance of recent deep learning approaches, two fundamenta…
Hierarchical Text-Guided Brain Tumor Segmentation via Sub-Region-Aware Prompts
Bahram Mohammadi, Ta Duc Huy, Afrouz Sheikholeslami +8
Brain tumor segmentation remains challenging because the three standard sub-regions, i.e., whole tumor (WT), tumor core (TC), and enhancing tumor (ET), often exhibit ambiguous visu…
Learning to Reason and Navigate: Parameter Efficient Action Planning with Large Language Models
Bahram Mohammadi, Ehsan Abbasnejad, Yuankai Qi +3
The remote embodied referring expression (REVERIE) task requires an agent to navigate through complex indoor environments and localize a remote object specified by high-level instr…
Augmented Commonsense Knowledge for Remote Object Grounding
Bahram Mohammadi, Yicong Hong, Yuankai Qi +3
The vision-and-language navigation (VLN) task necessitates an agent to perceive the surroundings, follow natural language instructions, and act in photo-realistic unseen environmen…
ClaRe: Practical Class Incremental Learning By Remembering Previous Class Representations
Bahram Mohammadi, Mohammad Sabokrou
This paper presents a practical and simple yet efficient method to effectively deal with the catastrophic forgetting for Class Incremental Learning (CIL) tasks. CIL tends to learn…
Image/Video Deep Anomaly Detection: A Survey
Bahram Mohammadi, Mahmood Fathy, Mohammad Sabokrou
The considerable significance of Anomaly Detection (AD) problem has recently drawn the attention of many researchers. Consequently, the number of proposed methods in this research…
G2D: Generate to Detect Anomaly
Masoud Pourreza, Bahram Mohammadi, Mostafa Khaki +3
In this paper, we propose a novel method for irregularity detection. Previous researches solve this problem as a One-Class Classification (OCC) task where they train a reference mo…
AutoIDS: Auto-encoder Based Method for Intrusion Detection System
Mohammed Gharib, Bahram Mohammadi, Shadi Hejareh Dastgerdi +1
Intrusion Detection System (IDS) is one of the most effective solutions for providing primary security services. IDSs are generally working based on attack signatures or by detecti…
End-to-End Adversarial Learning for Intrusion Detection in Computer Networks
Bahram Mohammadi, Mohammad Sabokrou
This paper presents a simple yet efficient method for an anomaly-based Intrusion Detection System (IDS). In reality, IDSs can be defined as a one-class classification system, where…