Computer Power Evaluation Datasets

We have selected the ImageNet validation set and the Flower dataset as benchmark standards for the image classification domain. These datasets provide a robust and diverse set of images, ensuring a comprehensive evaluation of model performance. For benchmark testing in the object detection domain, we utilize the COCO2012 validation set and the Road Voc dataset. These datasets are well-suited for assessing the accuracy and efficiency of object detection models in various real-world scenarios. In terms of models, ResNet and MobileNet have been chosen for image classification benchmarks due to their state-of-the-art architectures and proven performance. For object detection, YOLOV3 is employed, known for its speed and accuracy in detecting multiple objects in images, making it an ideal choice for testing object detection models. This comprehensive benchmark setup ensures reliable performance validation across multiple domains.