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.
A Comprehensive Survey of Deep Learning for Image Captioning
2019521 citationsFerdous Sohel, Hamid Laga et al.profile →
Image-Based 3D Object Reconstruction: State-of-the-Art and Trends in the Deep Learning Era
2019274 citationsHamid Laga, Mohammed Bennamoun et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Hamid Laga'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 Hamid Laga with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hamid Laga more than expected).
This network shows the impact of papers produced by Hamid Laga. 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 Hamid Laga. The network helps show where Hamid Laga may publish in the future.
Co-authorship network of co-authors of Hamid Laga
This figure shows the co-authorship network connecting the top 25 collaborators of Hamid Laga.
A scholar is included among the top collaborators of Hamid Laga 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 Hamid Laga. Hamid Laga is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Lu, Yijuan, Fuqing Duan, Yiwei Fan, et al.. (2016). SHREC'16 Track: 3D Sketch-Based 3D Shape Retrieval. Murdoch Research Repository (Murdoch University).8 indexed citations
11.
Chopin, Joshua, Stanley J. Miklavcic, & Hamid Laga. (2013). Selection of parameters in active contour models for automated plant phenotypic analysis. Murdoch Research Repository (Murdoch University).1 indexed citations
12.
Laga, Hamid & H. Takahashi. (2009). CUDA (Computer Unified Device Architecture). Murdoch Research Repository (Murdoch University).
13.
Laga, Hamid, et al.. (2009). Mouth region localization based on Gabor features and active appearance models. Murdoch Research Repository (Murdoch University).2 indexed citations
14.
Laga, Hamid & Miki Nakajima. (2007). Statistical spherical wavelet moments for Content-based 3D model retrieval. Murdoch Research Repository (Murdoch University).2 indexed citations
15.
Laga, Hamid, et al.. (2007). GPU-based shape silhouettes. Murdoch Research Repository (Murdoch University).1 indexed citations
16.
Laga, Hamid, Hiromasa Takahashi, & M. Nakajima. (2006). Spherical parameterization and geometry image-based 3D shape similarity estimation. Murdoch Research Repository (Murdoch University).3 indexed citations
17.
Laga, Hamid, Kazuo Chihara, & M. Nakajima. (2006). 3D model retrieval using spherical extent functions and wavelet descriptors. Murdoch Research Repository (Murdoch University).1 indexed citations
18.
Laga, Hamid & H. Takahashi. (2004). Geometry image based similarity estimation for 3D model retrieval. Murdoch Research Repository (Murdoch University).1 indexed citations
Zenati, Nadia, et al.. (1998). Contribution to restoration of degraded images. Murdoch Research Repository (Murdoch University).1 indexed citations
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.