Dataset for Fine-Tuning Code Generation Models: Kannada-English Algorithmic Statements and Python Code حسب Goutami Sooda (20714729)

The comparison experiment with state-of-the-art algorithms. حسب Manlin Zhu (21354237)

The comparison experiment of YOLO series algorithms. حسب Manlin Zhu (21354237)

Comparative results of each algorithm in comparative experiment. حسب Junhao Wei (6816803)

Iteration curves of different algorithms in comparison experiment. حسب Junhao Wei (6816803)

Relevant parameter settings for the algorithm proposed in the experiment. حسب Jinfeng Xiong (748277)

Data and code resources. حسب Sam Hall-McMaster (10343795)

Ablation experiment results of different algorithm models. حسب Peng Xiong (1459000)

Performance comparison experiments with mainstream object detection algorithms. حسب Dongshan Jiang (21866339)

The parameter setting of the evolutionary neural network. حسب Wenbing Shi (5806160)

الموضوعات:

The genome coding scheme. حسب Wenbing Shi (5806160)

الموضوعات:

The optimal number of clusters identified using the GMM clustering algorithm. حسب Dinh K. Tang (20469082)

Optimal number of clusters identified using the GMM clustering algorithm. حسب Dinh K. Tang (20469082)

The algorithm of the AWGE-ESPCA model. حسب Rui Miao (1592461)

Impact of multiunit merging on neural information encoding. حسب Daniel Suárez-Barrera (22676654)

الموضوعات:

Codes for "<b>A coherent power-load optimization algorithm for wind-farm-level yaw control considering wake effects via deep neural network</b>" حسب Yize Wang (19535173)

"…<p dir="ltr">Codes for "<b>A coherent power-load optimization algorithm for wind-farm-level yaw control considering wake effects via deep neural network</b>"</p>…"

code_4 حسب Olga Ovtsarenko (20432033)

The genetic algorithm. حسب Viktoria Zemliak (19500335)

USDA-ARS Tucson, Arizona 2014-2022 Data Reservoir of Field Experiments with Managed Honey Bee Colonies: Annotated Hive Frame Photos: Dataset I حسب Vladimir Kulyukin (21983990)

"…</p><p dir="ltr">SRC/ also contains the following Python scripts that we used for training YOLO networks:</p><p dir="ltr">(a) train_valid_split.py -- splits all alldata.txt in USDA_ARZ_DATA_YOLO_19june2025.zip into train.txt and valid.txt for YOLO training.…"

Flowchart of the algorithm. حسب Xingan Fu (21594713)