Texture classification is an important and challenging problem in many image processing applications.

The Brain Tumor Segmentation (BraTS) 2019 dataset provides 335 training subjects, 125 validation subjects and 167 testing ones, each with four MRI modality sequences (T1, T1ce,...

Skin lesion analysis toward melanoma detection 2018: A challenge hosted by the international skin imaging collaboration (isic).

The MoNuSeg dataset comprises 30 microscopic images from seven organs in the training set, with annotations of 21,623 individual nuclei, and 14 similar images in the test set.

The dataset used for testing the proposed next-best-view classification method.

The Mobile Features Dataset is used to test the proposed method.

AlexNet for time series classification

Infrasound data classification using neural networks

The dataset comprises of phone call records of a marketing campaign run by a Portuguese bank. The marital status of the clients is considered feature to ensure fairness.

The dataset used in the paper is a real-world 3D point cloud dataset, which is used for 3D shape classification, part segmentation, and shape retrieval tasks.

The Salinas dataset was acquired over the Salinas Valley in California and gathered by the AVIRIS sensor.

The CASIA dataset contains palmprint images from over 100 individuals, captured under various lighting conditions.

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...

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used it for language modeling and image classification tasks.

Point cloud registration is a crucial problem in computer vision and robotics. Existing methods either rely on matching local geometric features, which are sensitive to the pose...