4 citations · 8 across the 9 of their papers we have counts for
9 papers
Assessing Generalisation Capability of Machine Learning Models for Intrusion Detection
Md Zakir Hossain, Md Ayshik Rahman Khan, Md Rafiqul Islam +2
The growth of networked and IoT systems has intensified cyber-security threats and exposed the limits of traditional signature-based intrusion detection. Although machine-learning-…
MIP-GAF: A MLLM-annotated Benchmark for Most Important Person Localization and Group Context Understanding
Surbhi Madan, Shreya Ghosh, Lownish Rai Sookha +4
Estimating the Most Important Person (MIP) in any social event setup is a challenging problem mainly due to contextual complexity and scarcity of labeled data. Moreover, the causal…
What Does Softmax Probability Tell Us about Classifiers Ranking Across Diverse Test Conditions?
Weijie Tu, Weijian Deng, Liang Zheng +1
This work aims to develop a measure that can accurately rank the performance of various classifiers when they are tested on unlabeled data from out-of-distribution (OOD) distributi…
Authentic Emotion Mapping: Benchmarking Facial Expressions in Real News
Qixuan Zhang, Zhifeng Wang, Yang Liu +4
In this paper, we present a novel benchmark for Emotion Recognition using facial landmarks extracted from realistic news videos. Traditional methods relying on RGB images are resou…
A Closer Look at the Robustness of Contrastive Language-Image Pre-Training (CLIP)
Weijie Tu, Weijian Deng, Tom Gedeon
Contrastive Language-Image Pre-training (CLIP) models have demonstrated remarkable generalization capabilities across multiple challenging distribution shifts. However, there is st…
Optimizing Camera Configurations for Multi-View Pedestrian Detection
Yunzhong Hou, Xingjian Leng, Tom Gedeon +1
Jointly considering multiple camera views (multi-view) is very effective for pedestrian detection under occlusion. For such multi-view systems, it is critical to have well-designed…
AMF: Adaptable Weighting Fusion with Multiple Fine-tuning for Image Classification
Xuyang Shen, Jo Plested, Sabrina Caldwell +2
Fine-tuning is widely applied in image classification tasks as a transfer learning approach. It re-uses the knowledge from a source task to learn and obtain a high performance in t…
Strengthening Skeletal Action Recognizers via Leveraging Temporal Patterns
Zhenyue Qin, Pan Ji, Dongwoo Kim +3
Skeleton sequences are compact and lightweight. Numerous skeleton-based action recognizers have been proposed to classify human behaviors. In this work, we aim to incorporate compo…
How to Synthesize a Large-Scale and Trainable Micro-Expression Dataset?
Yuchi Liu, Zhongdao Wang, Tom Gedeon +1
This paper does not contain technical novelty but introduces our key discoveries in a data generation protocol, a database and insights. We aim to address the lack of large-scale d…