Some cultivars’ phenotype changed dramatically during their flower opening process [14], if labeled as the same cultivar will cause ambiguity, as shown in Fig. 1. These problems restrict the application of deep learning in plant phenotype. Fig. 1 Opening process of one large-flowered ...
The ImageNet dataset contains 14,197,122 annotated images according to the WordNet hierarchy. Since 2010 the dataset is used in the ImageNet Large Scale Visual Recognition Challenge (ILSVRC), a benchmark in image classification and object detection. The
Code for "bootstrap, review, decode: using out-of-domain textual data to improve image captioning" - Semi-Supervised-Image-Captioning/Data/flickr/captions_val.json at master · wenhuchen/Semi-Supervised-Image-Captioning
Hand holding a red can of soda labeled “FIZZ,” with water splashing out from the top. The bright blue sky with scattered clouds provides a refreshing and dynamic backdrop. STYLE Photography PROMPT editorial portrait of a women, looking slightly away from the camera, half of her is in full...
White and Brown Labeled Plastic Coffee Cup on Brown Tabletop Near Black Multimedia Player Black Corded Headset on White Table White and Black Cat Latte Macchiato , a close up shot Close-up of Car Forks on black Black and Red Apples on Brown Surface Black-and-white, Blur, Close-up...
Public flower classification dataset CLIP benchmarking Colab notebook CLIP repo Corresponding YouTube Assembling Your Dataset To try out CLIP, you will need to bring a dataset of images that you want classified, partitioned into the classes that you would like to see. If you do not already ...
<p id="sp0105" view="all"> Image/video stitching is a technology for solving the field of view (FOV) limitation of images/ videos. It stitches multiple overlapping images/videos to generate a wide-FOV image/video, and has been used in various fields such
detail, contrast, etc. we manually selected 2146 words related to objects such as eye, sky, face, ribbon, water, tree, flower, expression, hand, bird, glass, dog, hair, cat, smile, sun, window, car, etc. All of them can be avaiable at directory aesthetic_and_object_word in DPC2022...
However, the models presented in that chapter were built to classify an image as whole—they could not tell us where in the image a flower was. In this section, we will look at ways to build ML models that can provide this location information. This is a task known as object detection...
Even with the well-labeled datasets (e.gønedot, CelebA [35]), it is still a very challenging task to describe the manipulation mode directly on the pixels [20-23]. As a remedy, pre-trained GAN models provide yet another possible solution, where the disentanglement of latent spaces has ...