424 citations · 451 across the 16 of their papers we have counts for
16 papers
ShadowSense: Unsupervised Domain Adaptation and Feature Fusion for Shadow-Agnostic Tree Crown Detection from RGB-Thermal Drone Imagery
Rudraksh Kapil, Seyed Mojtaba Marvasti-Zadeh, Nadir Erbilgin +1
Accurate detection of individual tree crowns from remote sensing data poses a significant challenge due to the dense nature of forest canopy and the presence of diverse environment…
Adversarial Score-Based Generative Models for MMSE-achieving AmBC Channel Estimation
Fatemeh Rezaei, S. Mojtaba Marvasti-Zadeh, Chintha Tellambura +1
This letter presents a pioneering method that employs deep learning within a probabilistic framework for the joint estimation of both direct and cascaded channels in an ambient bac…
Training-based Model Refinement and Representation Disagreement for Semi-Supervised Object Detection
Seyed Mojtaba Marvasti-Zadeh, Nilanjan Ray, Nadir Erbilgin
Semi-supervised object detection (SSOD) aims to improve the performance and generalization of existing object detectors by utilizing limited labeled data and extensive unlabeled da…
Crown-CAM: Interpretable Visual Explanations for Tree Crown Detection in Aerial Images
Seyed Mojtaba Marvasti-Zadeh, Devin Goodsman, Nilanjan Ray +1
Visual explanation of ``black-box'' models allows researchers in explainable artificial intelligence (XAI) to interpret the model's decisions in a human-understandable manner. In t…
Early Detection of Bark Beetle Attack Using Remote Sensing and Machine Learning: A Review
Seyed Mojtaba Marvasti-Zadeh, Devin Goodsman, Nilanjan Ray +1
This paper provides a comprehensive review of past and current advances in the early detection of bark beetle-induced tree mortality from three primary perspectives: bark beetle &…
Classification of Bark Beetle-Induced Forest Tree Mortality using Deep Learning
Rudraksh Kapil, Seyed Mojtaba Marvasti-Zadeh, Devin Goodsman +2
Bark beetle outbreaks can dramatically impact forest ecosystems and services around the world. For the development of effective forest policies and management plans, the early dete…
Learning-based Monocular 3D Reconstruction of Birds: A Contemporary Survey
Seyed Mojtaba Marvasti-Zadeh, Mohammad N. S. Jahromi, Javad Khaghani +3
In nature, the collective behavior of animals, such as flying birds is dominated by the interactions between individuals of the same species. However, the study of such behavior am…
CHASE: Robust Visual Tracking via Cell-Level Differentiable Neural Architecture Search
Seyed Mojtaba Marvasti-Zadeh, Javad Khaghani, Li Cheng +2
A strong visual object tracker nowadays relies on its well-crafted modules, which typically consist of manually-designed network architectures to deliver high-quality tracking resu…
Adaptive Exploitation of Pre-trained Deep Convolutional Neural Networks for Robust Visual Tracking
Seyed Mojtaba Marvasti-Zadeh, Hossein Ghanei-Yakhdan, Shohreh Kasaei
Due to the automatic feature extraction procedure via multi-layer nonlinear transformations, the deep learning-based visual trackers have recently achieved great success in challen…
COMET: Context-Aware IoU-Guided Network for Small Object Tracking
Seyed Mojtaba Marvasti-Zadeh, Javad Khaghani, Hossein Ghanei-Yakhdan +2
We consider the problem of tracking an unknown small target from aerial videos of medium to high altitudes. This is a challenging problem, which is even more pronounced in unavoida…
Efficient Scale Estimation Methods using Lightweight Deep Convolutional Neural Networks for Visual Tracking
Seyed Mojtaba Marvasti-Zadeh, Hossein Ghanei-Yakhdan, Shohreh Kasaei
In recent years, visual tracking methods that are based on discriminative correlation filters (DCF) have been very promising. However, most of these methods suffer from a lack of r…
Beyond Background-Aware Correlation Filters: Adaptive Context Modeling by Hand-Crafted and Deep RGB Features for Visual Tracking
Seyed Mojtaba Marvasti-Zadeh, Hossein Ghanei-Yakhdan, Shohreh Kasaei
In recent years, the background-aware correlation filters have achie-ved a lot of research interest in the visual target tracking. However, these methods cannot suitably model the…
Effective Fusion of Deep Multitasking Representations for Robust Visual Tracking
Seyed Mojtaba Marvasti-Zadeh, Hossein Ghanei-Yakhdan, Shohreh Kasaei +2
Visual object tracking remains an active research field in computer vision due to persisting challenges with various problem-specific factors in real-world scenes. Many existing tr…
Deep Learning for Visual Tracking: A Comprehensive Survey
Seyed Mojtaba Marvasti-Zadeh, Li Cheng, Hossein Ghanei-Yakhdan +1
Visual target tracking is one of the most sought-after yet challenging research topics in computer vision. Given the ill-posed nature of the problem and its popularity in a broad r…
A Novel Boundary Matching Algorithm for Video Temporal Error Concealment
Seyed Mojtaba Marvasti-Zadeh, Hossein Ghanei-Yakhdan, Shohreh Kasaei
With the fast growth of communication networks, the video data transmission from these networks is extremely vulnerable. Error concealment is a technique to estimate the damaged da…
An Efficient Adaptive Boundary Matching Algorithm for Video Error Concealment
Seyed Mojtaba Marvasti-Zadeh, Hossein Ghanei-Yakhdan, Shohreh Kasaei
Sending compressed video data in error-prone environments (like the Internet and wireless networks) might cause data degradation. Error concealment techniques try to conceal the re…