17 citations · 36 across the 18 of their papers we have counts for
19 papers
Towards Open-World Object-based Anomaly Detection via Self-Supervised Outlier Synthesis
Brian K. S. Isaac-Medina, Yona Falinie A. Gaus, Neelanjan Bhowmik +1
Object detection is a pivotal task in computer vision that has received significant attention in previous years. Nonetheless, the capability of a detector to localise objects out o…
Performance Evaluation of Segment Anything Model with Variational Prompting for Application to Non-Visible Spectrum Imagery
Yona Falinie A. Gaus, Neelanjan Bhowmik, Brian K. S. Isaac-Medina +1
The Segment Anything Model (SAM) is a deep neural network foundational model designed to perform instance segmentation which has gained significant popularity given its zero-shot s…
Unaligned 2D to 3D Translation with Conditional Vector-Quantized Code Diffusion using Transformers
Abril Corona-Figueroa, Sam Bond-Taylor, Neelanjan Bhowmik +4
Generating 3D images of complex objects conditionally from a few 2D views is a difficult synthesis problem, compounded by issues such as domain gap and geometric misalignment. For…
Robust Semi-Supervised Anomaly Detection via Adversarially Learned Continuous Noise Corruption
Jack W Barker, Neelanjan Bhowmik, Yona Falinie A Gaus +1
Anomaly detection is the task of recognising novel samples which deviate significantly from pre-establishednormality. Abnormal classes are not present during training meaning that…
1st Workshop on Maritime Computer Vision (MaCVi) 2023: Challenge Results
Benjamin Kiefer, Matej Kristan, Janez Perš +70
The 1 Workshop on Maritime Computer Vision (MaCVi) 2023 focused on maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicle (USV), and…
Detecting Anomalies using Generative Adversarial Networks on Images
Rushikesh Zawar, Krupa Bhayani, Neelanjan Bhowmik +2
Automatic detection of anomalies such as weapons or threat objects in baggage security, or detecting impaired items in industrial production is an important computer vision task de…
Joint Sub-component Level Segmentation and Classification for Anomaly Detection within Dual-Energy X-Ray Security Imagery
Neelanjan Bhowmik, Toby P. Breckon
X-ray baggage security screening is in widespread use and crucial to maintaining transport security for threat/anomaly detection tasks. The automatic detection of anomaly, which is…
Lost in Compression: the Impact of Lossy Image Compression on Variable Size Object Detection within Infrared Imagery
Neelanjan Bhowmik, Jack W. Barker, Yona Falinie A. Gaus +1
Lossy image compression strategies allow for more efficient storage and transmission of data by encoding data to a reduced form. This is essential enable training with larger datas…
Semi-Supervised Surface Anomaly Detection of Composite Wind Turbine Blades From Drone Imagery
Jack. W. Barker, Neelanjan Bhowmik, Toby. P. Breckon
Within commercial wind energy generation, the monitoring and predictive maintenance of wind turbine blades in-situ is a crucial task, for which remote monitoring via aerial survey…
Operationalizing Convolutional Neural Network Architectures for Prohibited Object Detection in X-Ray Imagery
Thomas W. Webb, Neelanjan Bhowmik, Yona Falinie A. Gaus +1
The recent advancement in deep Convolutional Neural Network (CNN) has brought insight into the automation of X-ray security screening for aviation security and beyond. Here, we exp…
On the impact of using X-ray energy response imagery for object detection via Convolutional Neural Networks
Neelanjan Bhowmik, Yona Falinie A. Gaus, Toby P. Breckon
Automatic detection of prohibited items within complex and cluttered X-ray security imagery is essential to maintaining transport security, where prior work on automatic prohibited…
Efficient and Compact Convolutional Neural Network Architectures for Non-temporal Real-time Fire Detection
William Thomson, Neelanjan Bhowmik, Toby P. Breckon
Automatic visual fire detection is used to complement traditional fire detection sensor systems (smoke/heat). In this work, we investigate different Convolutional Neural Network (C…
Multi-Class 3D Object Detection Within Volumetric 3D Computed Tomography Baggage Security Screening Imagery
Qian Wang, Neelanjan Bhowmik, Toby P. Breckon
Automatic detection of prohibited objects within passenger baggage is important for aviation security. X-ray Computed Tomography (CT) based 3D imaging is widely used in airports fo…
On the Evaluation of Prohibited Item Classification and Detection in Volumetric 3D Computed Tomography Baggage Security Screening Imagery
Qian Wang, Neelanjan Bhowmik, Toby P. Breckon
X-ray Computed Tomography (CT) based 3D imaging is widely used in airports for aviation security screening whilst prior work on prohibited item detection focuses primarily on 2D X-…
Experimental Exploration of Compact Convolutional Neural Network Architectures for Non-temporal Real-time Fire Detection
Ganesh Samarth C. A., Neelanjan Bhowmik, Toby P. Breckon
In this work we explore different Convolutional Neural Network (CNN) architectures and their variants for non-temporal binary fire detection and localization in video or still imag…
Evaluating the Transferability and Adversarial Discrimination of Convolutional Neural Networks for Threat Object Detection and Classification within X-Ray Security Imagery
Yona Falinie A. Gaus, Neelanjan Bhowmik, Samet Akcay +1
X-ray imagery security screening is essential to maintaining transport security against a varying profile of threat or prohibited items. Particular interest lies in the automatic d…
On the Impact of Object and Sub-component Level Segmentation Strategies for Supervised Anomaly Detection within X-ray Security Imagery
Neelanjan Bhowmik, Yona Falinie A. Gaus, Samet Akcay +2
X-ray security screening is in widespread use to maintain transportation security against a wide range of potential threat profiles. Of particular interest is the recent focus on t…
The Good, the Bad and the Ugly: Evaluating Convolutional Neural Networks for Prohibited Item Detection Using Real and Synthetically Composited X-ray Imagery
Neelanjan Bhowmik, Qian Wang, Yona Falinie A. Gaus +2
Detecting prohibited items in X-ray security imagery is pivotal in maintaining border and transport security against a wide range of threat profiles. Convolutional Neural Networks…
Evaluation of a Dual Convolutional Neural Network Architecture for Object-wise Anomaly Detection in Cluttered X-ray Security Imagery
Yona Falinie A. Gaus, Neelanjan Bhowmik, Samet Akçay +3
X-ray baggage security screening is widely used to maintain aviation and transport security. Of particular interest is the focus on automated security X-ray analysis for particular…