37 citations · 122 across the 16 of their papers we have counts for
16 papers
BIOSCAN-5M: A Multimodal Dataset for Insect Biodiversity
Zahra Gharaee, Scott C. Lowe, ZeMing Gong +10
As part of an ongoing worldwide effort to comprehend and monitor insect biodiversity, this paper presents the BIOSCAN-5M Insect dataset to the machine learning community and establ…
Video Relationship Detection Using Mixture of Experts
Ala Shaabana, Zahra Gharaee, Paul Fieguth
Machine comprehension of visual information from images and videos by neural networks faces two primary challenges. Firstly, there exists a computational and inference gap in conne…
Implicit Causal Representation Learning via Switchable Mechanisms
Shayan Shirahmad Gale Bagi, Zahra Gharaee, Oliver Schulte +1
Learning causal representations from observational and interventional data in the absence of known ground-truth graph structures necessitates implicit latent causal representation…
Memory-Efficient Continual Learning Object Segmentation for Long Video
Amir Nazemi, Mohammad Javad Shafiee, Zahra Gharaee +1
Recent state-of-the-art semi-supervised Video Object Segmentation (VOS) methods have shown significant improvements in target object segmentation accuracy when information from pre…
A Step Towards Worldwide Biodiversity Assessment: The BIOSCAN-1M Insect Dataset
Zahra Gharaee, ZeMing Gong, Nicholas Pellegrino +13
In an effort to catalog insect biodiversity, we propose a new large dataset of hand-labelled insect images, the BIOSCAN-Insect Dataset. Each record is taxonomically classified by a…
Self-supervised learning of object pose estimation using keypoint prediction
Zahra Gharaee, Felix Järemo Lawin, Per-Erik Forssén
This paper describes recent developments in object specific pose and shape prediction from single images. The main contribution is a new approach to camera pose prediction by self-…
Generative Causal Representation Learning for Out-of-Distribution Motion Forecasting
Shayan Shirahmad Gale Bagi, Zahra Gharaee, Oliver Schulte +1
Conventional supervised learning methods typically assume i.i.d samples and are found to be sensitive to out-of-distribution (OOD) data. We propose Generative Causal Representation…
Machine Learning Challenges of Biological Factors in Insect Image Data
Nicholas Pellegrino, Zahra Gharaee, Paul Fieguth
The BIOSCAN project, led by the International Barcode of Life Consortium, seeks to study changes in biodiversity on a global scale. One component of the project is focused on study…
Predicting the intended action using internal simulation of perception
Zahra Gharaee
This article proposes an architecture, which allows the prediction of intention by internally simulating perceptual states represented by action pattern vectors. To this end, assoc…
Graph Representation Learning for Road Type Classification
Zahra Gharaee, Shreyas Kowshik, Oliver Stromann +1
We present a novel learning-based approach to graph representations of road networks employing state-of-the-art graph convolutional neural networks. Our approach is applied to real…
Action in Mind: A Neural Network Approach to Action Recognition and Segmentation
Zahra Gharaee
Recognizing and categorizing human actions is an important task with applications in various fields such as human-robot interaction, video analysis, surveillance, video retrieval,…
Online recognition of unsegmented actions with hierarchical SOM architecture
Zahra Gharaee
Automatic recognition of an online series of unsegmented actions requires a method for segmentation that determines when an action starts and when it ends. In this paper, a novel a…
Hierarchical growing grid networks for skeleton based action recognition
Zahra Gharaee
In this paper, a novel cognitive architecture for action recognition is developed by applying layers of growing grid neural networks.Using these layers makes the system capable of…
Online Recognition of Actions Involving Objects
Zahra Gharaee, Peter Gärdenfors, Magnus Johnsson
We present an online system for real time recognition of actions involving objects working in online mode. The system merges two streams of information processing running in parall…
First and Second Order Dynamics in a Hierarchical SOM system for Action Recognition
Zahra Gharaee, Peter Gärdenfors, Magnus Johnsson
Human recognition of the actions of other humans is very efficient and is based on patterns of movements. Our theoretical starting point is that the dynamics of the joint movements…
A Bayesian Approach to Reinforcement Learning of Vision-Based Vehicular Control
Zahra Gharaee, Karl Holmquist, Linbo He +1
In this paper, we present a state-of-the-art reinforcement learning method for autonomous driving. Our approach employs temporal difference learning in a Bayesian framework to lear…