Comparative results with existing representative algorithms. by Yan Qin (118276)

“…<p>Comparative results with existing representative algorithms.</p>…”

Comparative comparison between RSA algorithm, fuzzy RSA algorithm, algorithm. by Hanan Alolaiyan (18536236)

Scalability analysis comparing the near-linear algorithm and the naïve quadratic-time algorithm. by Paweł Górecki (3285255)

Subjects:

Ablation experiments. In the table, A represents the C2f-MLLA module, B represents the BiFPN-FFFN module, C represents the ShapeIoU module, and D represents the COA algorithm. by Jiayue Zhang (7832669)

“…<p>Ablation experiments. In the table, A represents the C2f-MLLA module, B represents the BiFPN-FFFN module, C represents the ShapeIoU module, and D represents the COA algorithm.…”

Scalability analysis comparing the near-linear algorithm and the naïve quadratic-time algorithm for small norms. by Paweł Górecki (3285255)

Subjects:

Parameter values of the compared algorithms. by Huimin Lu (4434682)

“…Finally, we proposed an escape Coati Optimization Algorithm (eCOA) for global optimization to enhance classification performance. …”

Scalability analysis comparing the near-linear algorithm (outlined bars) and the naïve quadratic-time algorithm on large trees. by Paweł Górecki (3285255)

Subjects:

Mean(SD) AUC-ROC for Study Population and Demographic Subgroups by Classification Algorithm. by Elizabeth A. Campbell (3019293)

Execution of t-intuitionistic fuzzy RSA algorithm. by Hanan Alolaiyan (18536236)

Value ranges of three representative points. by Bin Zhao (276445)

An instance of the IPP that can be solved by applying the algorithms for the DPP. by Jordan Moutet (21800145)

Subjects:

Comparison of Tracking Performance Among Different Improvement Methods with YOLOv5s (↓represents “Lower is better”, ↑ represents “Higher is better”). by Guofeng Qin (11025170)

Performance comparison of different optimization algorithms for global optimization. by Huimin Lu (4434682)

Central coronal slices for representative oscillation amplitude maps for the 3 algorithms and 3 participant groups investigated in this study. by Ivina Mali (12425544)

Comparison of algorithms on Guava. by Jing Wang (6206297)

Representative trials for three participants. by Kimberly A. Ingraham (20454993)

Clinical use algorithm. by Chibuike K. Uwakwe (22655742)

Algorithms included in Neuroptimus. by Máté Mohácsi (20469514)

Subjects:

(a) Comparison between SDNN and Traditional Methods. The horizontal axis represents the prediction horizon, while the vertical axis denotes computation time; red denotes traditional methods, and blue represents SDNN. (b) Comparison of different algorithms under different inputs. The horizontal axis represents algorithm type and total surrounding computation speed, with red lines indicating single input and blue lines representing multiple inputs. by Kai Sun (140584)

“…(b) Comparison of different algorithms under different inputs. The horizontal axis represents algorithm type and total surrounding computation speed, with red lines indicating single input and blue lines representing multiple inputs.…”

Representative photographic image. by Kengo Oka (1420585)