Samet Akcay

Orcid: 0000-0003-3334-7118

According to our database1, Samet Akcay authored at least 36 papers between 2016 and 2024.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
AUPIMO: Redefining Visual Anomaly Detection Benchmarks with High Speed and Low Tolerance.
CoRR, 2024

Divide and Conquer: High-Resolution Industrial Anomaly Detection via Memory Efficient Tiled Ensemble.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
Cascaded structure tensor for robust baggage threat detection.
Neural Comput. Appl., May, 2023

Unsupervised anomaly instance segmentation for baggage threat recognition.
J. Ambient Intell. Humaniz. Comput., March, 2023

Incremental Instance Segmentation for Cluttered Baggage Threat Detection.
Proceedings of the IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, 2023

2022
A Novel Incremental Learning Driven Instance Segmentation Framework to Recognize Highly Cluttered Instances of the Contraband Items.
IEEE Trans. Syst. Man Cybern. Syst., 2022

Towards automatic threat detection: A survey of advances of deep learning within X-ray security imaging.
Pattern Recognit., 2022

Tensor pooling-driven instance segmentation framework for baggage threat recognition.
Neural Comput. Appl., 2022

Anomalib: A Deep Learning Library for Anomaly Detection.
Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

2021
Multi-Modal Learning for Real-Time Automotive Semantic Foggy Scene Understanding via Domain Adaptation.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2021

Competitive Simplicity for Multi-Task Learning for Real-Time Foggy Scene Understanding via Domain Adaptation.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2021

Autoencoders Without Reconstruction for Textural Anomaly Detection.
Proceedings of the International Joint Conference on Neural Networks, 2021

2020
Towards real-time anomaly detection within X-ray security imagery: self-supervised adversarial training approach.
PhD thesis, 2020

Meta-Transfer Learning Driven Tensor-Shot Detector for the Autonomous Localization and Recognition of Concealed Baggage Threats.
Sensors, 2020

Multi-Model Learning for Real-Time Automotive Semantic Foggy Scene Understanding via Domain Adaptation.
CoRR, 2020

Trainable Structure Tensors for Autonomous Baggage Threat Detection Under Extreme Occlusion.
CoRR, 2020

Cascaded Structure Tensor Framework for Robust Identification of Heavily Occluded Baggage Items from X-ray Scans.
CoRR, 2020

Detecting Prohibited Items in X-Ray Images: a Contour Proposal Learning Approach.
Proceedings of the IEEE International Conference on Image Processing, 2020

Exploring Racial Bias within Face Recognition via per-subject Adversarially-Enabled Data Augmentation.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
Multi-Task Regression-based Learning for Autonomous Unmanned Aerial Vehicle Flight Control within Unstructured Outdoor Environments [dataset].
Dataset, July, 2019

Multi-Task Regression-Based Learning for Autonomous Unmanned Aerial Vehicle Flight Control Within Unstructured Outdoor Environments.
IEEE Robotics Autom. Lett., 2019

Generative adversarial framework for depth filling via Wasserstein metric, cosine transform and domain transfer.
Pattern Recognit., 2019

Online Deep Reinforcement Learning for Autonomous UAV Navigation and Exploration of Outdoor Environments.
CoRR, 2019

Deep CMST Framework for the Autonomous Recognition of Heavily Occluded and Cluttered Baggage Items from Multivendor Security Radiographs.
CoRR, 2019

Multi-Task Learning for Automotive Foggy Scene Understanding via Domain Adaptation to an Illumination-Invariant Representation.
CoRR, 2019

Evaluation of a Dual Convolutional Neural Network Architecture for Object-wise Anomaly Detection in Cluttered X-ray Security Imagery.
Proceedings of the International Joint Conference on Neural Networks, 2019

Skip-GANomaly: Skip Connected and Adversarially Trained Encoder-Decoder Anomaly Detection.
Proceedings of the International Joint Conference on Neural Networks, 2019

Evaluating the Transferability and Adversarial Discrimination of Convolutional Neural Networks for Threat Object Detection and Classification within X-Ray Security Imagery.
Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

On the Impact of Object and Sub-Component Level Segmentation Strategies for Supervised Anomaly Detection within X-Ray Security Imagery.
Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

2018
Using Deep Convolutional Neural Network Architectures for Object Classification and Detection Within X-Ray Baggage Security Imagery.
IEEE Trans. Inf. Forensics Secur., 2018

On the Impact of Illumination-Invariant Image Pre-transformation for Contemporary Automotive Semantic Scene Understanding.
Proceedings of the 2018 IEEE Intelligent Vehicles Symposium, 2018

On the Impact of Varying Region Proposal Strategies for Raindrop Detection and Classification Using Convolutional Neural Networks.
Proceedings of the 2018 IEEE International Conference on Image Processing, 2018

GANomaly: Semi-supervised Anomaly Detection via Adversarial Training.
Proceedings of the Computer Vision - ACCV 2018, 2018

2017
An evaluation of region based object detection strategies within X-ray baggage security imagery.
Proceedings of the 2017 IEEE International Conference on Image Processing, 2017

2016
Transfer learning using convolutional neural networks for object classification within X-ray baggage security imagery.
Proceedings of the 2016 IEEE International Conference on Image Processing, 2016

On using feature descriptors as visual words for object detection within X-ray baggage security screening.
Proceedings of the 7th International Conference on Imaging for Crime Detection and Prevention, 2016


  Loading...