The dataset used for training and validation of the proposed approach to combine semantic segmentation and dense outlier detection.

A labeled dataset for Malayalam Sign Language (MSL) letters and signs for the identification of static hand gestures specific to Malayalam Sign Language from real-time videos.

The MNIST and CIFAR10 datasets are used to evaluate the Cycle-Consistent Adversarial GAN (CycleAdvGAN) for image classification.

NIH CXR database for lung segmentation, including CXR images with severe abnormal findings.

Montgomery database for lung segmentation, including CXR images with small- or medium-sized abnormal findings.

JSRT database for lung segmentation, including CXR images with small- or medium-sized abnormal findings.

The Bollywood dataset is a collection of images of Bollywood celebrities with varying body mass indexes (BMIs). The dataset is used for face-to-BMI prediction.

Three publicly available BMI annotated facial image datasets assembled from social media, namely, VisualBMI, VIP-Attributes, and Bollywood datasets.

MIMIC-CXR is a comprehensive collection of de-identified Chest X-ray (CXR) data acquired from Beth Israel Deaconess Medical Center in Boston, United States. MIMIC-CXR includes...

Ultrasound dataset for Achilles tendon healing progress estimation

The dataset used in this paper is a CNN training dataset, specifically VGG-16, VGG-19, and AlexNet.

Large scale datasets [18, 17, 27, 6] boosted text conditional image generation quality. However, in some domains it could be difficult to make such datasets and usually it could...

The MNIST dataset (Lecun et al., 1998), which consists of 60,000 gray-scale images of handwritten digits. Each image has an accompanying label in {0, 1,..., 9}, and is stored as...

Sensor fusion can significantly improve the performance of many computer vision tasks. However, traditional fusion approaches are either not data-driven and cannot exploit prior...

Sensor fusion can significantly improve the performance of many computer vision tasks. However, traditional fusion approaches are either not data-driven and cannot exploit prior...

Sensor fusion can significantly improve the performance of many computer vision tasks. However, traditional fusion approaches are either not data-driven and cannot exploit prior...

The CIFAR-10 dataset consists of 60,000 training images and 10,000 test images. Each image is a 32×32 color image.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the CLIP model and the CIFAR-10 and ImageNet datasets.

Large scale datasets [18, 17, 27, 6] boosted text conditional image generation quality. However, in some domains it could be difficult to make such datasets and usually it could...