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20222026
most citedDeep Active Learning in the Presence of Label Noise: A Survey

3 citations · 7 across the 10 of their papers we have counts for

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cs.CV2026

Front-to-Back: Benchmarking Vision-Language Models for Asymmetric Cross-View Vehicle Re-Identification

Moseli Mots'oehli, Thulani Babeli

Matching the same vehicle across front and rear cameras is difficult because the cameras do not share a view and the vehicle's appearance changes substantially. We introduce Front2…

cs.CV2025

Simulating Refractive Distortions and Weather-Induced Artifacts for Resource-Constrained Autonomous Perception

Moseli Mots'oehli, Feimei Chen, Hok Wai Chan +4

The scarcity of autonomous vehicle datasets from developing regions, particularly across Africa's diverse urban, rural, and unpaved roads, remains a key obstacle to robust percepti…

cs.CV2025

Balancing Accuracy, Calibration, and Efficiency in Active Learning with Vision Transformers Under Label Noise

Moseli Mots'oehli, Hope Mogale, Kyungim Baek

Fine-tuning pre-trained convolutional neural networks on ImageNet for downstream tasks is well-established. Still, the impact of model size on the performance of vision transformer…

cs.CV2024

GCI-ViTAL: Gradual Confidence Improvement with Vision Transformers for Active Learning on Label Noise

Moseli Mots'oehli, kyungim Baek

Active learning aims to train accurate classifiers while minimizing labeling costs by strategically selecting informative samples for annotation. This study focuses on image classi…

cs.CV2024

Assistive Image Annotation Systems with Deep Learning and Natural Language Capabilities: A Review

Moseli Mots'oehli

While supervised learning has achieved significant success in computer vision tasks, acquiring high-quality annotated data remains a bottleneck. This paper explores both scholarly…

cs.CV2024

FishNet: Deep Neural Networks for Low-Cost Fish Stock Estimation

Moseli Mots'oehli, Anton Nikolaev, Wawan B. IGede +3

Fish stock assessment often involves manual fish counting by taxonomy specialists, which is both time-consuming and costly. We propose FishNet, an automated computer vision system…

cs.CV2022★ 2 cited

Public Parking Spot Detection And Geo-localization Using Transfer Learning

Moseli Mots'oehli, Yao Chao Yang

In cities around the world, locating public parking lots with vacant parking spots is a major problem, costing commuters time and adding to traffic congestion. This work illustrate…