1 citations · 1 across the 2 of their papers we have counts for
6 papers
Visual-Prompt Guided Wildlife Instance-Level Recognition
Mufhumudzi Muthivhi, Jiahao Huo, Terence van Zyl +1
Fine-grained wildlife re-identification remains a challenging area in research. Current state-of-the-art approaches apply a detection and re-identification pipeline. We propose a o…
Complexity of Linear Regions in Self-supervised Deep ReLU Networks
Mufhumudzi Muthivhi, Terence L. van Zyl
There has been growing interest in studying the complexity of Rectified Linear Unit (ReLU) based activation networks. Recent work investigates the evolution of the number of piecew…
Improving Wildlife Out-of-Distribution Detection: Africas Big Five
Mufhumudzi Muthivhi, Jiahao Huo, Fredrik Gustafsson +1
Mitigating human-wildlife conflict seeks to resolve unwanted encounters between these parties. Computer Vision provides a solution to identifying individuals that might escalate in…
BiCoRec: Bias-Mitigated Context-Aware Sequential Recommendation Model
Mufhumudzi Muthivhi, Terence L van Zyl, Hairong Wang
Sequential recommendation models aim to learn from users evolving preferences. However, current state-of-the-art models suffer from an inherent popularity bias. This study develope…
Nearest-Class Mean and Logits Agreement for Wildlife Open-Set Recognition
Jiahao Huo, Mufhumudzi Muthivhi, Terence L. van Zyl +1
Current state-of-the-art Wildlife classification models are trained under the closed world setting. When exposed to unknown classes, they remain overconfident in their predictions.…
Wildlife Target Re-Identification Using Self-supervised Learning in Non-Urban Settings
Mufhumudzi Muthivhi, Terence L. van Zyl
Wildlife re-identification aims to match individuals of the same species across different observations. Current state-of-the-art (SOTA) models rely on class labels to train supervi…