ITDAV-25 (Indian Thermal Dataset for Autonomous Vehicles), a thermal image dataset specifically curated to advance research in Advanced Driver Assistance Systems (ADAS), particularly for environments characterized by low visibility, night-time conditions, and inclement weather. The dataset comprises of 13,688 raw thermal images, collected without any synthetic augmentation techniques.
The Reflectance Transformation Imaging dataset consists of 32 images from the squeeze of the inscription "Hymn of Kouretes" or "Hymn of Palaikastron" (fragment A, side A) which is hosted at the Archaeological Museum of Heracleon, Crete. The resulting .PTM file is also available, which opens with the free software RTI Viewer.
In today’s world, deaf and mute person face many problems in their daily life due to miscommunication as well as misunderstanding. These problems have existed since long ago but are ultimately being solved with the introduction of Hand sign language. There exist many different sign languages such as ASL, ISL, etc. But for regional and low-resource languages like Mizo, the state language of Mizoram, spoken by the northeastern people in India, not much research has been done on the advancement of sign language based on the Mizo language.
In today’s world, deaf and mute person face many problems in their daily life due to miscommunication as well as misunderstanding. These problems have existed since long ago but are ultimately being solved with the introduction of Hand sign language. There exist many different sign languages such as ASL, ISL, etc. But for regional and low-resource languages like Mizo, the state language of Mizoram, spoken by the northeastern people in India, not much research has been done on the advancement of sign language based on the Mizo language.
The dataset comprises a diverse collection of images featuring windows alongside various artificial light sources, such as bulbs, LEDs, and tube lights. Each image captures the interplay of natural and artificial illumination, offering a rich visual spectrum that encompasses different lighting scenarios. This compilation is invaluable for applications ranging from architectural design and interior decor to computer vision and image processing.
The problem of effective disposal of the trash generated by people has rightfully attracted major interest from various sections of society in recent times. Recently, deep learning solutions have been proposed to design automated mechanisms to segregate waste. However, most datasets used for this purpose are not adequate. In this paper, we introduce a new dataset, TrashBox, containing 17,785 images across seven different classes, including medical and e-waste classes which are not included in any other existing dataset.
This dataset contains solar radiation data at the high resolution of 1 second for consecutive 72 hours under dynamic weather conditions (sunny and cloudy days). This data can be useful in various fields and researchers can use it in their research for algorithms validation and performance evaluation.
A crowdsourcing subjective evaluation of viewport images obtained with several sphere-to-plane projections was conducted. The viewport images were rendered from eight omnidirectional images in equirectangular format. The pairwise comparison (PC) method was chosen for the subjective evaluation of projections. More details about the viewport images and subjective evaluation procedure can be found in [1].
The 5K EPP Dataset includes 5007 photos of water crystaks classified in 13 categories. This dataset was created under the leaderhip of Prof. Masaru Emoto.
ETFP (Eye-Tracking and Fixation Points) consists of two eye-tracking datasets: EToCVD (Eye-Tracking of Colour Vision Deficiencies) and ETTO (Eye-Tracking Through Objects). The former is a collection of images, their corresponding eye-movement coordinates and the fixation point maps, obtained by involving two cohorts, respectively, people with and without CVD (Colour Vision Deficiencies). The latter collects images with just one object laying on a homogeneous background, the corresponding eye-movement coordinates and fixation point maps gathered during eye-tracking sessions.
