3.6.2.4 Performance Characterization in Computer Vision

Chapter Contents (Back)
Performance. Evaluation.
See also Explainable Aritficial Intelligence.

Haralick, R.M.[Robert M.],
Performance Characterization in Computer Vision,
CVGIP(60), No. 2, September 1994, pp. 245-249.
DOI Link BibRef 9409
Earlier: CAIP93(1-9).
Springer DOI 9309
BibRef
Earlier: BMVC92(1-8).
PDF File. BibRef
Earlier:
Methodology for Experimental Computer Vision,
CVPR89(437-438).
IEEE DOI Dialogue. Methodological issues in evaluating performance. BibRef

Cinque, L., Guerra, C., Levialdi, S.,
Performance Characterization in Computer Vision: Reply,
CVGIP(60), No. 2, September 1994, pp. 250-252.
DOI Link BibRef 9409

Weng, J.Y., Huang, T.S.,
Performance of Computer Vision Algorithms: Reply,
CVGIP(60), No. 2, September 1994, pp. 253-256.
DOI Link BibRef 9409

Meer, P.,
Computer Vision -- The Goal and the Means: Reply,
CVGIP(60), No. 2, September 1994, pp. 257-259.
DOI Link BibRef 9409

Shirai, Y.,
Performance Characterization in Computer Vision: Reply,
CVGIP(60), No. 2, September 1994, pp. 260-261.
DOI Link BibRef 9409

Draper, B.A., Beveridge, J.R.,
Performance Characterization in Computer Vision: Reply,
CVGIP(60), No. 2, September 1994, pp. 262-263.
DOI Link BibRef 9409

Haralick, R.M.,
Performance Characterization in Computer Vision: Reply,
CVGIP(60), No. 2, September 1994, pp. 264-265.
DOI Link BibRef 9409

Zhuang, Y.[Yan], Yu, J.H.[Jun-Hao], Liu, Q.[Qi], Sun, Y.X.[Yu-Xuan], Li, J.T.[Jia-Tong], Huang, Z.Y.[Zhen-Ya], Chen, E.[Enhong],
Efficient Benchmarking via Bias-Bounded Subset Selection,
PAMI(47), No. 12, December 2025, pp. 11785-11801.
IEEE DOI 2511
Benchmark testing, Artificial intelligence, Costs, Computational modeling, Biological system modeling, Measurement, subset selection BibRef

Komorniczak, J.[Joanna], Ksieniewicz, P.[Pawel], Zyblewski, P.[Pawel],
Structuring the processing frameworks for data stream evaluation and application,
PR(172), 2026, pp. 112516.
Elsevier DOI 2512
Data stream, Concept drift, Concept drift detection, Classification, Label delay, Fair experimental evaluation BibRef


Horváth, J.[János],
ECO-AI: Energy-Conscious Optimization for AI Training,
ReGenAI25(5266-5270)
IEEE DOI 2512
Training, Renewable energy sources, Analytical models, Biological system modeling, Text to image, Performance metrics, Carbon footprint BibRef

Gustafson, L.[Laura], Rolland, C.[Chloe], Ravi, N.[Nikhila], Duval, Q.[Quentin], Adcock, A.[Aaron], Fu, C.Y.[Cheng-Yang], Hall, M.[Melissa], Ross, C.[Candace],
FACET: Fairness in Computer Vision Evaluation Benchmark,
ICCV23(20313-20325)
IEEE DOI Code:
WWW Link. 2401
BibRef

Gao, I.[Irena], Ilharco, G.[Gabriel], Lundberg, S.[Scott], Ribeiro, M.T.[Marco Tulio],
Adaptive Testing of Computer Vision Models,
ICCV23(3980-3991)
IEEE DOI 2401
BibRef

Jain, A.[Achin], Swaminathan, G.[Gurumurthy], Favaro, P.[Paolo], Yang, H.[Hao], Ravichandran, A.[Avinash], Harutyunyan, H.[Hrayr], Achille, A.[Alessandro], Dabeer, O.[Onkar], Schiele, B.[Bernt], Swaminathan, A.[Ashwin], Soatto, S.[Stefano],
A Meta-Learning Approach to Predicting Performance and Data Requirements,
CVPR23(3623-3632)
IEEE DOI 2309
BibRef

Tu, W.J.[Wei-Jie], Deng, W.J.[Wei-Jian], Gedeon, T.[Tom], Zheng, L.[Liang],
A Bag-of-Prototypes Representation for Dataset-Level Applications,
CVPR23(2881-2892)
IEEE DOI 2309
BibRef

Mao, C.Z.[Cheng-Zhi], Teotia, R.[Revant], Sundar, A.[Amrutha], Menon, S.[Sachit], Yang, J.F.[Jun-Feng], Wang, X.[Xin], Vondrick, C.[Carl],
Doubly Right Object Recognition: A Why Prompt for Visual Rationales,
CVPR23(2722-2732)
IEEE DOI 2309
the metric requires the model to simultaneously produce both the right labels as well as the right rationales BibRef

Arriaga, O.[Octavio], Palacio, S.[Sebastian], Valdenegro-Toro, M.[Matias],
Difficulty Estimation with Action Scores for Computer Vision Tasks,
LXCV23(245-253)
IEEE DOI 2309
BibRef

Chapter on Books, Collections, Overviews, General, and Surveys continues in
Geometry of Visual Space .


Last update:Jan 8, 2026 at 12:52:16