12 citations · 14 across the 7 of their papers we have counts for
9 papers
Semi-Supervised Adaptation of Vision-Language Models for Image Classification
Mohamed L. Mekhalfi, Mohamad M. Al Rahhal, Yakoub Bazi +4
Vision-language models like CLIP have shown sig- nificant potential in handling natural images, yet their perfor- mance is often limited by the distinct characteristics of satellit…
An analysis of vision-language models for fabric retrieval
Francesco Giuliari, Asif Khan Pattan, Mohamed Lamine Mekhalfi +1
Effective cross-modal retrieval is essential for applications like information retrieval and recommendation systems, particularly in specialized domains such as manufacturing, wher…
The RaspGrade Dataset: Towards Automatic Raspberry Ripeness Grading with Deep Learning
Mohamed Lamine Mekhalfi, Paul Chippendale, Fabio Poiesi +3
This research investigates the application of computer vision for rapid, accurate, and non-invasive food quality assessment, focusing on the novel challenge of real-time raspberry…
Orange Quality Grading with Deep Learning
Mohamed Lamine Mekhalfi, Paul Chippendale, Francisco Fraile +1
Orange grading is a crucial step in the fruit industry, as it helps to sort oranges according to different criteria such as size, quality, ripeness, and health condition, ensuring…
Leveraging Confident Image Regions for Source-Free Domain-Adaptive Object Detection
Mohamed Lamine Mekhalfi, Davide Boscaini, Fabio Poiesi
Source-free domain-adaptive object detection is an interesting but scarcely addressed topic. It aims at adapting a source-pretrained detector to a distinct target domain without re…
Wild Berry image dataset collected in Finnish forests and peatlands using drones
Luigi Riz, Sergio Povoli, Andrea Caraffa +13
Berry picking has long-standing traditions in Finland, yet it is challenging and can potentially be dangerous. The integration of drones equipped with advanced imaging techniques r…
Detect, Augment, Compose, and Adapt: Four Steps for Unsupervised Domain Adaptation in Object Detection
Mohamed L. Mekhalfi, Davide Boscaini, Fabio Poiesi
Unsupervised domain adaptation (UDA) plays a crucial role in object detection when adapting a source-trained detector to a target domain without annotated data. In this paper, we p…
The MONET dataset: Multimodal drone thermal dataset recorded in rural scenarios
Luigi Riz, Andrea Caraffa, Matteo Bortolon +11
We present MONET, a new multimodal dataset captured using a thermal camera mounted on a drone that flew over rural areas, and recorded human and vehicle activities. We captured MON…
A Sparse Representation of Complete Local Binary Pattern Histogram for Human Face Recognition
Mawloud Guermoui, Mohamed L. Mekhalfi
Human face recognition has been a long standing problem in computer vision and pattern recognition. Facial analysis can be viewed as a two-fold problem, namely (i) facial represent…