Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Underwater scene prior inspired deep underwater image and video enhancement
This map shows the geographic impact of Fatih Porikli's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Fatih Porikli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fatih Porikli more than expected).
This network shows the impact of papers produced by Fatih Porikli. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Fatih Porikli. The network helps show where Fatih Porikli may publish in the future.
Co-authorship network of co-authors of Fatih Porikli
This figure shows the co-authorship network connecting the top 25 collaborators of Fatih Porikli.
A scholar is included among the top collaborators of Fatih Porikli based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Fatih Porikli. Fatih Porikli is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Zanjani, Farhad Ghazvinian, et al.. (2021). Modality-Agnostic Topology Aware Localization. neural information processing systems. 34.4 indexed citations
5.
Bhalgat, Yash, et al.. (2020). Structured Convolutions for Efficient Neural Network Design. Neural Information Processing Systems. 33. 5553–5564.1 indexed citations
6.
Naseer, Muzammal, Salman Khan, Muhammad Haris Khan, Fahad Shahbaz Khan, & Fatih Porikli. (2019). Cross-Domain Transferability of Adversarial Perturbations. Neural Information Processing Systems. 32. 12885–12895.6 indexed citations
Jodoin, Pierre‐Marc, et al.. (2012). Changedetection.net: A new change detection benchmark dataset. ANU Open Research (Australian National University). 1–8.578 indexed citations breakdown →
16.
Ruta, Andrzej, et al.. (2009). A new approach for in-vehicle camera traffic sign detection and recognition. 509–513.22 indexed citations
17.
Joshi, Ajay J., Fatih Porikli, & Nikolaos Papanikolopoulos. (2009). Multi-class active learning for image classification. 2009 IEEE Conference on Computer Vision and Pattern Recognition. 2372–2379.352 indexed citations breakdown →
18.
Bebis, George, Richard Boyle, Bahram Parvin, et al.. (2008). Proceedings of the 4th International Symposium on Advances in Visual Computing.4 indexed citations
19.
Bashir, Faisal & Fatih Porikli. (2006). Performance evaluation of object detection and tracking systems.78 indexed citations
20.
Porikli, Fatih. (2005). Integral histogram: a fast way to extract histograms in Cartesian spaces. 829–836 vol. 1.481 indexed citations breakdown →
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.