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Found 8 papers, 4 papers with code
Pedestrian Detection in Low-Light Conditions: A Comprehensive Survey
Pedestrian detection remains a critical problem in various domains, such as computer vision, surveillance, and autonomous driving.
CAPRI: Context-Aware Interpretable Point-of-Interest Recommendation Framework
Point-of-Interest (POI ) recommendation systems have gained popularity for their unique ability to suggest geographical destinations with the incorporation of contextual information such as time, location, and user-item interaction.
A Robust Pedestrian Detection Approach for Autonomous Vehicles
Moreover, the experiments on the Caltech pedestrian dataset samples have verified that our proposed approach is an effective and accurate method for pedestrian detection and can outperform other existing methodologies.
Visual SLAM: What are the Current Trends and What to Expect?
In this regard, Visual Simultaneous Localization and Mapping (VSLAM) methods refer to the SLAM approaches that employ cameras for pose estimation and map generation.
Exploring the Impact of Temporal Bias in Point-of-Interest Recommendation
Recommending appropriate travel destinations to consumers based on contextual information such as their check-in time and location is a primary objective of Point-of-Interest (POI) recommender systems.
The Unfairness of Active Users and Popularity Bias in Point-of-Interest Recommendation
This paper studies the interplay between (i) the unfairness of active users, (ii) the unfairness of popular items, and (iii) the accuracy (personalization) of recommendation as three angles of our study triangle.
From SLAM to Situational Awareness: Challenges and Survey
The capability of a mobile robot to efficiently and safely perform complex missions is limited by its knowledge of the environment, namely the situation.
Iranis: A Large-scale Dataset of Farsi License Plate Characters
This paper introduces a large-scale dataset that includes images of numbers and characters used in Iranian car license plates.
