Search Results for author: Sahand Sharifzadeh

Found 16 papers, 11 papers with code

MemeGraphs: Linking Memes to Knowledge Graphs

1 code implementation28 May 2023 Vasiliki Kougia, Simon Fetzel, Thomas Kirchmair, Erion Çano, Sina Moayed Baharlou, Sahand Sharifzadeh, Benjamin Roth

In this work, we propose to use scene graphs, that express images in terms of objects and their visual relations, and knowledge graphs as structured representations for meme classification with a Transformer-based architecture.

Entity Linking Knowledge Graphs +1

Prior-RadGraphFormer: A Prior-Knowledge-Enhanced Transformer for Generating Radiology Graphs from X-Rays

1 code implementation24 Mar 2023 Yiheng Xiong, Jingsong Liu, Kamilia Zaripova, Sahand Sharifzadeh, Matthias Keicher, Nassir Navab

The extraction of structured clinical information from free-text radiology reports in the form of radiology graphs has been demonstrated to be a valuable approach for evaluating the clinical correctness of report-generation methods.

Decision Making Multi-Label Classification +1

Ultra-High-Resolution Detector Simulation with Intra-Event Aware GAN and Self-Supervised Relational Reasoning

1 code implementation7 Mar 2023 Hosein Hashemi, Nikolai Hartmann, Sahand Sharifzadeh, James Kahn, Thomas Kuhr

Simulating high-resolution detector responses is a storage-costly and computationally intensive process that has long been challenging in particle physics.

Conditional Image Generation Density Estimation +4

Do DALL-E and Flamingo Understand Each Other?

no code implementations23 Dec 2022 Hang Li, Jindong Gu, Rajat Koner, Sahand Sharifzadeh, Volker Tresp

To study this question, we propose a reconstruction task where Flamingo generates a description for a given image and DALL-E uses this description as input to synthesize a new image.

Image Captioning Image Reconstruction +2

The Tensor Brain: A Unified Theory of Perception, Memory and Semantic Decoding

1 code implementation27 Sep 2021 Volker Tresp, Sahand Sharifzadeh, Hang Li, Dario Konopatzki, Yunpu Ma

Although memory appears to be about the past, its main purpose is to support the agent in the present and the future.

Decision Making Self-Supervised Learning

Improving Scene Graph Classification by Exploiting Knowledge from Texts

no code implementations9 Feb 2021 Sahand Sharifzadeh, Sina Moayed Baharlou, Martin Schmitt, Hinrich Schütze, Volker Tresp

We show that by fine-tuning the classification pipeline with the extracted knowledge from texts, we can achieve ~8x more accurate results in scene graph classification, ~3x in object classification, and ~1. 5x in predicate classification, compared to the supervised baselines with only 1% of the annotated images.

General Classification Graph Classification +7

Classification by Attention: Scene Graph Classification with Prior Knowledge

no code implementations19 Nov 2020 Sahand Sharifzadeh, Sina Moayed Baharlou, Volker Tresp

A major challenge in scene graph classification is that the appearance of objects and relations can be significantly different from one image to another.

General Classification Graph Classification +5

PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings

2 code implementations28 Jul 2020 Mehdi Ali, Max Berrendorf, Charles Tapley Hoyt, Laurent Vermue, Sahand Sharifzadeh, Volker Tresp, Jens Lehmann

Recently, knowledge graph embeddings (KGEs) received significant attention, and several software libraries have been developed for training and evaluating KGEs.

 Ranked #1 on Link Prediction on WN18 (training time (s) metric)

Knowledge Graph Embedding Knowledge Graph Embeddings +1

The Tensor Brain: Semantic Decoding for Perception and Memory

no code implementations29 Jan 2020 Volker Tresp, Sahand Sharifzadeh, Dario Konopatzki, Yunpu Ma

In particular, we propose that explicit perception and declarative memories require a semantic decoder, which, in a simple realization, is based on four layers: First, a sensory memory layer, as a buffer for sensory input, second, an index layer representing concepts, third, a memoryless representation layer for the broadcasting of information ---the "blackboard", or the "canvas" of the brain--- and fourth, a working memory layer as a processing center and data buffer.

Knowledge Graphs

Improving Visual Relation Detection using Depth Maps

1 code implementation2 May 2019 Sahand Sharifzadeh, Sina Moayed Baharlou, Max Berrendorf, Rajat Koner, Volker Tresp

We argue that depth maps can additionally provide valuable information on object relations, e. g. helping to detect not only spatial relations, such as standing behind, but also non-spatial relations, such as holding.

Relationship Detection Visual Relationship Detection

Learning to Drive using Inverse Reinforcement Learning and Deep Q-Networks

no code implementations12 Dec 2016 Sahand Sharifzadeh, Ioannis Chiotellis, Rudolph Triebel, Daniel Cremers

We propose an inverse reinforcement learning (IRL) approach using Deep Q-Networks to extract the rewards in problems with large state spaces.

Autonomous Driving reinforcement-learning +1

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